Experiment 3: Document at various level for large dataset(COVID-science: non-science : covid-psychology (20 papers))

1. Article level

In the file each article is seperated by 'NEW_PAPER' in 'covid-scienc.txt' and 'NEW NEWSPAPER' in 'covid-non-science'.

#import
import os.path
from gensim import corpora
from gensim.models import LsiModel
from nltk.tokenize import RegexpTokenizer
from nltk.corpus import stopwords
from nltk.stem.porter import PorterStemmer
from gensim.models.coherencemodel import CoherenceModel
import matplotlib.pyplot as plt
import pandas as pd
import numpy as np
import sklearn as s
import dataframe_image as dfi

C:\ProgramData\Anaconda3\lib\site-packages\gensim\similarities\__init__.py:15: UserWarning: The gensim.similarities.levenshtein submodule is disabled, because the optional Levenshtein package <https://pypi.org/project/python-Levenshtein/> is unavailable. Install Levenhstein (e.g. `pip install python-Levenshtein`) to suppress this warning.
  warnings.warn(msg)

covid-science.txt

def load_data(path,file_name,seperator):
    """
    Input  : path and file_name
    Purpose: loading text file
    Output : list of paragraphs/documents and
             title(initial 100 words considred as title of document)
    """
    documents_list = []
    titles=[]
    document = ''
    i=0
    with open( os.path.join(path, file_name) ,"r", encoding="utf8") as fin:
        data = fin.read()
        words = data.split()
        fin.seek(0)
        print('Number of words in text file :', len(words))
        for line in fin.readlines():
            text = line.strip()
            i=i+1
            if text !='':
                document = document+text
                if text == seperator:
                    documents_list.append(document)
                    document = ''
        documents_list.append(document)
    print("Total Number of Documents:",len(documents_list))
    titles.append( text[0:min(len(text),100)] )
    return documents_list,titles,len(words)

document_list,titles,word_count=load_data("","covid-science.txt",'NEW_PAPER')

Number of words in text file : 120257
Total Number of Documents: 20

def preprocess_data(doc_set):
    """
    Input  : docuemnt list
    Purpose: preprocess text (tokenize, removing stopwords, and stemming)
    Output : preprocessed text
    """
    # initialize regex tokenizer
    tokenizer = RegexpTokenizer(r'\w+')
    # create English stop words list
    en_stop = set(stopwords.words('english'))
    # Create p_stemmer of class PorterStemmer
    p_stemmer = PorterStemmer()
    # list for tokenized documents in loop
    texts = []
    # loop through document list
    for i in doc_set:
        # clean and tokenize document string
        raw = i.lower()
        tokens = tokenizer.tokenize(raw)
        tokens = [i for i in tokens if len(i)>4]
        print(tokens)
        # remove stop words from tokens
        stopped_tokens = [i for i in tokens if not i in en_stop]
        # stem tokens
        stemmed_tokens = [p_stemmer.stem(i) for i in stopped_tokens]
        # add tokens to list
        texts.append(stemmed_tokens)
    return texts

clean_text=preprocess_data(document_list)

['covidgr', 'dataset', 'covid', 'sdnetmethodology', 'predicting', 'covid', '19based', 'chest', 'imagess', 'tabik', 'gómez', 'martín', 'rodríguez', 'sevillano', 'garcía', 'charte', 'guirado', 'suárez', 'luengo', 'valero', 'gonzález', 'garcía', 'villanova', 'olmedo', 'sánchez', 'herreraabstract', 'currently', 'coronavirus', 'disease', 'covid', 'infectious', 'diseases', 'century', 'diagnosed', 'using', 'testing', 'scans', 'orchest', 'images', 'computed', 'tomography', 'scanners', 'testing', 'available', 'mostmedical', 'centers', 'hence', 'cases', 'imagesbecome', 'effective', 'assisting', 'clinicians', 'making', 'decisions', 'learning', 'neural', 'networkshave', 'great', 'potential', 'building', 'covid', 'triage', 'systemsand', 'detecting', 'covid', 'patients', 'especially', 'patients', 'withlow', 'severity', 'unfortunately', 'current', 'databases', 'allowbuilding', 'systems', 'highly', 'heterogeneousand', 'biased', 'towards', 'severe', 'cases', 'article', 'threefold', 'demystify', 'sensitivities', 'achieved', 'bymost', 'recent', 'covid', 'classification', 'models', 'under', 'aclose', 'collaboration', 'hospital', 'universitario', 'clínico', 'sancecilio', 'granada', 'spain', 'built', 'covidgr', 'homogeneous', 'balanced', 'database', 'includes', 'levelsmanuscript', 'received', 'september', 'revised', 'october', 'accepted', 'november', 'publication', 'november', 'current', 'version', 'december', 'supported', 'bythe', 'project', 'deepscop', 'ayudas', 'fundación', 'equipos', 'investigación', 'científica', 'covid19_rx', 'ayudas', 'fundaciónbbva', 'equipos', 'investigación', 'científica', 'covid', '192020', 'spanish', 'ministry', 'science', 'technology', 'under', 'theproject', 'tin2017', '89517', 'tabik', 'supported', 'ramon', 'cajalprogramme', '18136', 'gómez', 'supported', 'thefpu', 'programme', 'fpu16', '04765', 'charte', 'supported', 'fpuprogramme', 'fpu17', '04069', 'suárez', 'supported', 'programme', 'fpu18', '05989', 'supported', 'european', 'researchcouncil', 'grant', 'agreement', '647038', 'biodesert', 'projectis', 'approved', 'provincial', 'research', 'ethics', 'committee', 'granada', 'corresponding', 'author', 'siham', 'tabik', 'tabik', 'gómez', 'sevillano', 'garcía', 'charte', 'suárez', 'luengo', 'herrera', 'andalusian', 'research', 'institute', 'indata', 'science', 'computational', 'intelligence', 'university', 'granada', '18071', 'granada', 'spain', 'siham', 'anabelgrios', 'decsai', 'isega24ivan', 'gmail', 'fdavidcl', 'jlsuarezdiaz', 'julianlm', 'decsai', 'herrera', 'decsai', 'martín', 'rodríguez', 'valero', 'gonzález', 'garcía', 'villanova', 'olmedo', 'sánchez', 'hospital', 'universitario', 'clínicosan', 'cecilio', 'granada', '36310', 'spain', 'joseluismartin', 'hotmail', 'valerogonzalez', 'yahoo', 'pgvillanova', 'gmail', 'euolm', 'yahoo', 'atlanttic', 'research', 'center', 'telecommunication', 'technologies', 'university', 'galicia', 'spain', 'mreyarea', 'gmail', 'guirado', 'multidisciplinary', 'institute', 'environmentstudies', 'ramón', 'margalef', 'university', 'alicante', '03690', 'spain', 'geesecillo', 'gmail', 'digital', 'object', 'identifier', '3037127of', 'severity', 'normal', 'positive', 'moderate', 'severe', 'covidgr', 'contains', 'positive', 'and426', 'negative', 'posteroanterior', 'views', 'wepropose', 'covid', 'smart', 'based', 'network', 'covid', 'sdnet', 'methodology', 'improving', 'generalization', 'capacity', 'ofcovid', 'classification', 'models', 'approach', 'reaches', 'goodand', 'stable', 'results', 'accuracy', 'severe', 'moderate', 'andmild', 'covid', 'severity', 'levels', 'approach', 'could', 'inthe', 'early', 'detection', 'covid', 'covidgr', 'along', 'withthe', 'severity', 'level', 'labels', 'available', 'scientific', 'community', 'through', 'https', 'dasci', 'transferencia', 'covidgr', 'index', 'terms', 'covid', 'convolutional', 'neural', 'networks', 'smart', 'introductionin', 'months', 'world', 'witnessing', 'howcovid', 'pandemic', 'increasingly', 'infecting', 'large', 'massof', 'people', 'everywhere', 'world', 'trends', 'arenot', 'clear', 'research', 'confirm', 'problem', 'maypersist', 'until', 'besides', 'prevalence', 'studies', 'conducted', 'inseveral', 'countries', 'reveal', 'proportion', 'populationhave', 'developed', 'antibodies', 'after', 'exposure', 'virus', 'spain', 'means', 'frequently', 'large', 'number', 'patientswill', 'assessed', 'small', 'intervals', 'numberof', 'clinicians', 'resources', 'general', 'covid', 'diagnosis', 'carried', 'using', 'leastone', 'these', 'three', 'tests', 'computed', 'tomography', 'scans', 'based', 'assessment', 'itconsists', 'analyzing', 'radiographic', 'images', 'different', 'angles', 'needed', 'equipment', 'assessmentis', 'available', 'hospitals', 'takes', 'than15', 'minutes', 'patient', 'addition', 'required', 'forct', 'decontamination', '2reverse', 'transcription', 'polymerase', 'chain', 'reaction', 'rtpcr', 'detects', 'viral', 'sputum', 'online', 'available', 'https', 'english', 'elpais', 'society', 'antibody', 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'fully', 'automated', 'because', 'accuracyof', 'parsing', 'extracting', 'cannot', 'always', 'guaranteedby', 'using', 'current', 'packages', 'hence', 'users', 'intervenein', 'quality', 'control', 'process', 'image', 'typedata', 'product', 'quality', 'therapid', 'development', 'parsing', 'images', 'keepupdating', 'component', 'minimize', 'human', 'interventionin', 'automation', 'process']

def prepare_corpus(doc_clean):
    """
    Input  : clean document
    Purpose: create term dictionary of our courpus and Converting list of documents (corpus) into Document Term Matrix
    Output : term dictionary and Document Term Matrix
    """
    # Creating the term dictionary of our courpus, where every unique term is assigned an index. dictionary = corpora.Dictionary(doc_clean)
    dictionary = corpora.Dictionary(doc_clean)
    # Converting list of documents (corpus) into Document Term Matrix using dictionary prepared above.
    doc_term_matrix = [dictionary.doc2bow(doc) for doc in doc_clean]
    # generate LDA model
    return dictionary,doc_term_matrix

def create_gensim_lsa_model(doc_clean,number_of_topics,words):
    """
    Input  : clean document, number of topics and number of words associated with each topic
    Purpose: create LSA model using gensim
    Output : return LSA model
    """
    dictionary,doc_term_matrix=prepare_corpus(doc_clean)
    # generate LSA model
    lsamodel = LsiModel(doc_term_matrix, num_topics=number_of_topics, id2word = dictionary)  # train model
    #print(lsamodel.print_topics(num_topics=number_of_topics, num_words=words))
    return lsamodel

# LSA Model
number_of_topics=1
words=word_count
model=create_gensim_lsa_model(clean_text,number_of_topics,words)
words_from_science =dict(model.show_topic(0, topn=words))##dict and encoding matrix values

dict(model.show_topic(0, topn=5))

{'covid': 0.5195000201940307,
 'imag': 0.3819419924959869,
 'model': 0.2441435717675279,
 'dataset': 0.1784613020969509,
 'class': 0.1529705981881784}

from wordcloud import WordCloud
text = dict(model.show_topic(0, topn=20))
l=list(text.keys())
wordcloud = WordCloud(width=150, height=200,max_font_size=25, max_words=20, background_color="white").generate(" ".join(l))
plt.imshow(wordcloud, interpolation='bilinear')
plt.axis("off")
plt.savefig('graph12.png')

# LSA Model
number_of_topics = 20 #
words = word_count
model = create_gensim_lsa_model(clean_text,number_of_topics,words)

a=pd.DataFrame()

for i in range(number_of_topics):
    words_science =dict(model.show_topic(i, topn=words))
    b=pd.DataFrame(words_science,index=[i])
    a=a.append(b)

a=a.transpose()

top_words = dict(model.show_topic(0,topn=5))

df = pd.DataFrame(columns=list(top_words.keys()), 
                  index = list(top_words.keys()))

l = list(top_words.keys())
print('cosine-similarity')
for i in l:
    for j in l:
            matrix=np.array([a.loc[i],a.loc[j]])
            n = s.metrics.pairwise.cosine_similarity(matrix, matrix, dense_output=True)
            df.loc[[i],[j]] = n[0,1]
print(df)

dfi.export(df, 'df_styled15.png')

cosine-similarity
             covid       imag       model     dataset      class
covid            1   0.114718   0.0699065  -0.0721506   0.275795
imag      0.114718          1   -0.101632    0.179926  0.0364016
model    0.0699065  -0.101632           1  0.00335218   0.049745
dataset -0.0721506   0.179926  0.00335218           1  0.0568222
class     0.275795  0.0364016    0.049745   0.0568222          1

covid-non-science.txt

document_list,titles,word_count=load_data("","covid-non-science.txt",'NEW NEWSPAPER')

Number of words in text file : 8713
Total Number of Documents: 20

clean_text=preprocess_data(document_list)

['covid', 'recovery', 'covid', 'realityby', 'reuterspublished', 'updated', '2020by', 'joneslondon', 'reuters', 'world', 'shares', 'inched', 'towards', 'month', 'friday', 'industrial', 'bellwether', 'metal', 'copper', 'longest', 'weekly', 'winning', 'streak', 'nearly', 'three', 'years', 'recovering', 'global', 'nagging', 'coronavirus', 'nerves', 'market', 'rally', 'fuelled', 'record', 'numbers', 'largely', 'blown', 'itself', 'spike', 'covid', 'cases', 'though', 'fastest', 'expansion', 'china', 'services', 'sector', 'decade', 'stimulus', 'ensured', 'optimism', 'remained', 'chinese', 'shares', 'charged', 'their', 'highest', 'level', 'years', 'helping', 'asian', 'indexes', 'month', 'peaks', 'sight', 'european', 'markets', 'stalling', 'early', 'traders', 'surprise', 'currency', 'commodity', 'markets', 'subdued', 'after', 'otherwise', 'strong', 'confidence', 'sensitive', 'stalwarts', 'copper', 'sterling', 'australian', 'dollar', 'which', 'struggled', 'friday', 'think', 'infection', 'rates', 'fears', 'localised', 'lockdowns', 'doused', 'enthusiasm', 'societe', 'generale', 'strategist', 'jukes', 'three', 'elements', 'vaccine', 'hopes', 'decent', 'places', 'return', 'infection', 'rates', 'which', 'nervous', 'against', 'basket', 'currencies', 'dollar', 'slightly', 'early', 'london', 'trading', 'still', 'firmly', 'track', 'biggest', 'weekly', 'since', 'first', 'though', 'gained', 'against', 'swiss', 'franc', 'versus', 'sometimes', 'commodity', 'driven', 'norwegian', 'crown', 'futures', 'volumes', 'lower', 'usual', 'markets', 'holiday', 'friday', 'independence', 'nonfarm', 'payrolls', 'surged', 'million', 'above', 'average', 'forecast', 'million', 'thanks', 'rises', 'hospitality', 'sectors', 'economists', 'noted', 'there', 'caveats', 'upbeat', 'headline', 'figures', 'number', 'permanent', 'losers', 'continued', 'increasing', 'million', 'while', 'unemployment', 'remains', 'chunky', 'percentage', 'points', 'above', 'february', 'level', 'deutsche', 'analysis', 'unemployment', 'behind', 'developed', 'market', 'peers', 'barring', 'canada', 'recovery', 'faces', 'headwinds', 'surge', 'coronavirus', 'infections', 'prompts', 'states', 'delay', 'cases', 'reverse', 'plans', 'stores', 'reopen', 'activities', 'resume', 'three', 'dozen', 'states', 'increases', 'covid', 'cases', 'cases', 'florida', 'spiking', 'above', 'nevertheless', 'markets', 'largely', 'overlooking', 'spikes', 'taking', 'overall', 'situation', 'still', 'improving', 'overall', 'german', 'government', 'yields', 'basis', 'points', 'their', 'biggest', 'weekly', 'month', 'though', 'nudged', 'friday', 'riskier', 'italian', 'yields', 'though', 'which', 'their', 'lowest', 'since', 'march', 'prices', 'eased', 'after', 'otherwise', 'solid', 'brent', 'crude', 'barrel', 'while', 'crude', 'dropped', 'barrel', 'around', 'months', 'copper', 'prices', 'poised', 'seventh', 'consecutive', 'weekly', 'their', 'longest', 'winning', 'streak', 'nearly', 'three', 'years', 'despite', 'slight', 'easing', 'after', 'supplier', 'chile', 'assured', 'traders', 'about', 'supply', 'three', 'month', 'copper', 'hovering', 'tonne', 'ploughed', 'march', 'issue', 'hangs', 'markets', 'surge', 'secondary', 'infections', 'trigger', 'second', 'national', 'rather', 'regional', 'shutdowns', 'malcolm', 'freeman', 'director', 'kingdom', 'futures', 'wrote', 'reporting', 'jones', 'newspaper']
['covid', 'vaccine', 'frontrunnersby', 'reuterspublished', 'october', 'updated', 'october', '2020oct', 'reuters', 'pfizer', 'could', 'november', 'authorization', 'covid', 'vaccine', 'developing', 'opening', 'possibility', 'vaccine', 'being', 'available', 'united', 'states', 'moderna', 'astrazeneca', 'close', 'behind', 'largest', 'drugmaker', 'likely', 'early', 'their', 'vaccine', 'candidates', 'before', 'potential', 'vaccines', 'being', 'developed', 'tested', 'globally', 'covid', 'pandemic', 'human', 'trials', 'according', 'world', 'health', 'organization', 'following', 'tracks', 'candidates', 'final', 'stages', 'testing', 'separate', 'factbox', 'coronavirus', 'vaccines', 'under', 'development', 'click', 'company', 'stage', 'development', 'expected', 'doses', 'pfizer', 'stage', 'trials', 'underway', 'option', 'biontech', 'pfizer', 'earlier', 'october', 'could', 'emergency', 'authorization', 'november', 'indicating', 'vaccine', 'could', 'potentially', 'available', 'additional', 'canada', 'specified', 'japan', 'moderna', 'completed', 'enrollment', 'option', 'subjects', 'stage', 'trial', 'additional', 'interim', 'results', 'trial', 'expected', 'november', 'japan', 'distributed', 'takeda', 'canada', 'specified', 'johnson', 'johnson', 'large', 'vaccine', 'trial', 'resume', 'after', 'paused', 'under', 'subsequent', 'agreement', 'illness', 'study', 'volunteer', 'results', 'trial', 'expected', 'option', 'early', 'additional', 'canada', 'japan', 'applicable', 'astrazeneca', 'stage', 'trials', 'underway', 'supply', 'deals', 'countries', 'oxford', 'university', 'trial', 'vaccine', 'candidate', 'doses', 'pause', 'since', 'after', 'patient', 'trial', 'results', 'expected', 'coming', 'weeks', 'commitment', 'deliver', 'total', 'least', 'additional', 'italy', 'germany', 'netherlands', 'france', 'additional', 'canada', 'japan', 'sinovac', 'biotech', 'stage', 'trials', 'brazil', 'vaccine', 'approved', 'emergency', 'indonesia', 'turkey', 'underway', 'china', 'supply', 'prelim', 'expected', 'november', 'indonesia', 'least', 'doses', 'before', 'gamaleya', 'research', 'stage', 'trial', 'covid', 'people', 'inoculated', 'institute', 'vaccine', 'sputnik', 'underway', 'russia', 'supply', 'deals', 'since', 'prelim', 'countries', 'including', 'india', 'expected', 'november', 'brazil', 'saudi', 'arabia', 'doses', 'cansino', 'biologics', 'vaccine', 'candidate', 'final', 'stage', 'mexico', 'doses', 'early', 'trials', 'approved', 'chinese', 'military', 'stage', 'trial', 'underway', 'pakistan', 'sinopharm', 'group', 'stage', 'trials', 'expects', 'produce', 'underway', 'billion', 'doses', 'reporting', 'dania', 'nadeem', 'mrinalika', 'bengaluru', 'editing', 'ankur', 'banerjee', 'samuel', 'newspaper']
['giants', 'another', 'covid', 'caseby', 'reuterspublished', 'november', 'updated', 'november', '2020the', 'giants', 'another', 'covid', 'monday', 'night', 'notified', 'player', 'tested', 'positive', 'covid', 'giants', 'announced', 'tuesday', 'morning', 'player', 'immediately', 'isolated', 'contact', 'tracing', 'process', 'initiated', 'close', 'contacts', 'staff', 'members', 'identified', 'informed', 'remain', 'today', 'giants', 'entering', 'their', 'second', 'player', 'positive', 'covid', 'prior', 'playing', 'tampa', 'buccaneers', 'offensive', 'lineman', 'hernandez', 'tested', 'positive', 'hernandez', 'spent', 'nearly', 'weeks', 'reserve', 'covid', 'returned', 'played', 'sunday', 'victory', 'philadelphia', 'eagles', 'field', 'level', 'medianew', 'newspaper']
['covid', 'antivirals', 'taskforce', 'launchedby', 'mediapublished', 'april', 'updated', 'april', '2021at', 'covid', 'treatments', 'being', 'sought', 'government', 'experts', 'speed', 'recovery', 'people', 'become', 'infected', 'virus', 'government', 'taskforce', 'supercharge', 'search', 'antiviral', 'medications', 'covid', 'prime', 'minister', 'boris', 'johnson', 'group', 'medicines', 'covid', 'tracks', 'hoped', 'antivirals', 'could', 'reduce', 'infections', 'limit', 'impact', 'variants', 'protect', 'people', 'cannot', 'vaccines', 'those', 'fully', 'protected', 'after', 'having', 'officials', 'bring', 'treatments', 'online', 'could', 'people', 'covid', 'those', 'close', 'contact', 'could', 'offered', 'antiviral', 'medication', 'offered', 'tablet', 'infection', 'spreading', 'speed', 'recovery', 'antivirals', 'taskforce', 'which', 'appoint', 'chair', 'search', 'promising', 'potential', 'antiviral', 'medicines', 'which', 'taken', 'taskforce', 'support', 'development', 'drugs', 'through', 'clinical', 'trials', 'manufacturing', 'opportunities', 'antiviral', 'drugs', 'medication', 'specifically', 'treating', 'viral', 'infections', 'killing', 'preventing', 'growth', 'viruses', 'success', 'vaccination', 'programme', 'demonstrated', 'achieve', 'bring', 'together', 'brightest', 'minds', 'johnson', 'antivirals', 'taskforce', 'develop', 'innovative', 'treatments', 'covid', 'tracks', 'these', 'could', 'provide', 'another', 'vital', 'defence', 'against', 'future', 'increase', 'infections', 'lives', 'health', 'secretary', 'hancock', 'medicines', 'vital', 'weapon', 'protect', 'loved', 'terrible', 'virus', 'modelled', 'success', 'vaccines', 'therapeutics', 'taskforces', 'which', 'played', 'crucial', 'response', 'pandemic', 'bringing', 'together', 'supercharge', 'search', 'antiviral', 'treatments', 'autumn', 'government', 'chief', 'scientific', 'adviser', 'patrick', 'vallance', 'speed', 'which', 'vaccines', 'therapeutics', 'dexamethasone', 'identified', 'deployed', 'against', 'covid', 'critical', 'pandemic', 'response', 'antivirals', 'tablet', 'another', 'response', 'could', 'protect', 'those', 'protected', 'ineligible', 'vaccines', 'could', 'another', 'layer', 'defence', 'variants', 'concern', 'nikita', 'kanani', 'medical', 'director', 'primary', 'england', 'research', 'reality', 'record', 'speed', 'during', 'pandemic', 'taskforce', 'identify', 'convenient', 'treatments', 'patients', 'covid', 'commenting', 'announcement', 'penny', 'visiting', 'professor', 'pharmaceutical', 'medicine', 'kings', 'college', 'london', 'antiviral', 'treatment', 'influenza', 'shown', 'reduce', 'hospitalisation', 'prevent', 'death', 'epidemic', 'pandemic', 'waves', 'similar', 'preferably', 'simple', 'antiviral', 'suitable', 'community', 'range', 'interventions', 'critical', 'enable', 'remain', 'covid', 'pandemic', 'event', 'emergence', 'viral', 'variants', 'insensitive', 'vaccines', 'there', 'number', 'early', 'phase', 'trials', 'looking', 'antiviral', 'medications', 'newspaper']
['african', 'covid', 'deaths', '000by', 'afppublished', 'february', 'updated', 'february', '2021africa', 'thursday', 'recorded', 'deaths', 'covid', 'milestone', 'likely', 'understate', 'continent', 'billion', 'people', 'battles', 'second', 'infections', 'countries', 'region', 'death', 'reported', 'cases', 'according', 'tally', 'continent', 'relatively', 'spared', 'pandemic', 'except', 'oceania', 'reach', 'threshold', 'deaths', 'which', 'europe', 'crossed', 'april', 'south', 'africa', 'worst', 'african', 'country', 'rolled', 'testing', 'campaign', 'start', 'pandemic', 'country', 'recorded', 'nearly', 'million', 'cases', 'deaths', 'those', 'figures', 'based', 'daily', 'reports', 'communicated', 'health', 'authorities', 'reflect', 'fraction', 'actual', 'health', 'specialists', 'cases', 'clearly', 'under', 'reported', 'because', 'access', 'healthcare', 'facilities', 'under', 'reporting', 'milder', 'cases', 'south', 'african', 'virologist', 'barry', 'schoub', 'member', 'scientific', 'council', 'south', 'african', 'ministry', 'health', 'understaffed', 'health', 'facilities', 'means', 'meant', 'african', 'countries', 'unable', 'testing', 'countries', 'mainly', 'tests', 'capitals', 'further', 'moves', 'urban', 'centres', 'there', 'tests', 'explained', 'french', 'epidemiologist', 'emmanuel', 'baron', 'doctors', 'without', 'borders', 'disease', 'unnoticed', 'asymptomatic', 'patients', 'symptoms', 'confused', 'others', 'added', 'covid', 'found', 'pawpaw', 'zimbabwe', 'country', 'devastated', 'economy', 'mismanaged', 'health', 'system', 'hospitals', 'filled', 'covid', 'patients', 'exhausted', 'doctors', 'overwhelmed', 'nurses', 'official', 'number', 'cases', 'remains', 'tanzania', 'stopped', 'testing', 'after', 'claiming', 'found', 'positive', 'covid', 'pawpaw', 'quail', 'tanzanian', 'government', 'released', 'official', 'figures', 'april', 'someone', 'continent', 'would', 'deaths', 'infection', 'probably', 'would', 'believed', 'nkengasong', 'africa', 'director', 'centers', 'disease', 'control', 'preventions', 'reporters', 'thursday', 'africa', 'however', 'significantly', 'lower', 'europe', 'world', 'affected', 'region', 'deaths', 'recorded', 'other', 'regions', 'badly', 'latin', 'america', 'deaths', 'united', 'states', 'canada', 'deaths', 'after', 'sharp', 'increase', 'january', 'africa', 'figures', 'fallen', 'sharply', 'weeks', 'seven', 'continent', 'recorded', 'deaths', 'percent', 'previous', 'height', 'pandemic', 'january', 'continent', 'deaths', 'disaster', 'while', 'coronavirus', 'figures', 'clearly', 'underestimated', 'health', 'disaster', 'africa', 'baron', 'several', 'studies', 'antibodies', 'which', 'possible', 'detect', 'whether', 'person', 'recovered', 'previously', 'exposed', 'virus', 'underway', 'african', 'countries', 'should', 'provide', 'better', 'impact', 'pandemic', 'region', 'south', 'africa', 'where', 'almost', 'latest', 'cases', 'attributed', 'variant', 'virus', 'known', 'contagious', 'which', 'spread', 'widely', 'represents', 'nearly', 'deaths', 'reported', 'cases', 'continent', 'other', 'african', 'countries', 'affected', 'egypt', 'deaths', 'cases', 'morocco', 'deaths', 'cases', 'south', 'africa', 'country', 'covid', 'fatalities', 'continent', 'counting', 'deaths', 'inhabitants', 'ahead', 'tunisia', 'deaths', 'eswatini', 'lagging', 'behind', 'vaccination', 'continent', 'leading', 'industrial', 'powerhouse', 'administered', 'first', 'vaccines', 'wednesday', 'globally', 'covid', 'caused', 'million', 'infections', 'million', 'deaths', 'since', 'start', 'epidemic', 'wuhan', 'china', 'december', 'harnew', 'newspaper']
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['covid', 'restrictions', 'easing', 'nswby', 'australian', 'associated', 'presspublished', 'september', 'updated', 'september', '2020nsw', 'easing', 'covid', 'restrictions', 'around', 'school', 'community', 'lower', 'community', 'acquired', 'covid', 'numbers', 'weddings', 'people', 'official', 'wedding', 'party', 'dance', 'floor', 'where', 'previously', 'bride', 'groom', 'permittedschools', 'interschool', 'activities', 'resume', 'saturday', 'covid', 'safety', 'school', 'sport', 'return', 'normal', 'parents', 'school', 'sites', 'playing', 'instruments', 'singing', 'chanting', 'permitted', 'strict', 'restrictions', 'formals', 'graduations', 'permitted', 'school', 'formals', 'permitted', 'after', 'kindergarten', 'orientation', 'transition', 'excursions', 'camps', 'resume', 'strict', 'guidelines', 'school', 'choirs', 'musical', 'ensembles', 'resume', 'players', 'metre', 'distance', 'another', 'three', 'metres', 'players', 'reeded', 'woodwind', 'instruments', 'community', 'languages', 'schools', 'program', 'resume', 'learning', 'sport', 'parent', 'attend', 'community', 'sporting', 'activities', 'physical', 'distancing', 'least', 'metres', 'maintained', 'accommodation', 'facilities', 'overnight', 'event', 'organisers', 'implement', 'covid', 'safety', 'carpooling', 'should', 'continue', 'avoidednew', 'newspaper']
['zealand', 'launches', 'covid', 'diary', 'appby', 'australian', 'associated', 'presspublished', 'updated', '2020belatedly', 'cases', 'covid', 'zealand', 'government', 'launched', 'covid', 'kiwis', 'track', 'their', 'movements', 'prime', 'minister', 'jacinda', 'ardern', 'launched', 'wednesday', 'labelling', 'digital', 'diary', 'differs', 'australian', 'version', 'linking', 'other', 'users', 'instead', 'allows', 'kiwis', 'check', 'different', 'venues', 'cafes', 'restaurants', 'avoid', 'onerous', 'writing', 'contact', 'details', 'every', 'place', 'visited', 'helps', 'users', 'about', 'their', 'movements', 'ardern', 'people', 'keeps', 'themselves', 'rather', 'adding', 'broader', 'repository', 'might', 'business', 'stage', 'government', 'authorities', 'though', 'functionality', 'added', 'update', 'month', 'different', 'functionality', 'means', 'there', 'threshold', 'required', 'useful', 'still', 'plenty', 'kiwis', 'taken', 'before', 'officially', 'launched', 'kiwis', 'almost', 'population', 'downloaded', 'wednesday', 'director', 'general', 'health', 'ashley', 'bloomfield', 'announced', 'there', 'cases', 'covid', 'zealand', 'fourth', 'there', 'cases', 'overall', 'fortnight', 'decreasing', 'numbers', 'nightclubs', 'first', 'since', 'march', 'thursday', 'provided', 'customers', 'seated', 'groups', 'under', 'receive', 'table', 'service', 'ardern', 'further', 'review', 'gathering', 'numbers', 'currently', 'except', 'funerals', 'which', 'monday', 'cabinet', 'meeting', 'regularly', 'adjust', 'settings', 'allow', 'activity', 'ardern', 'showing', 'virus', 'squashed', 'months', 'zealander', 'being', 'treated', 'hospital', 'covid', 'require', 'intensive', 'newspaper']
['records', 'covid', 'cases', 'deathsby', 'reuterspublished', 'updated', '2021london', 'reuters', 'britain', 'reported', 'daily', 'covid', 'cases', 'government', 'figures', 'showed', 'thursday', 'slightly', 'reported', 'before', 'which', 'highest', 'daily', 'total', 'since', 'february', 'britain', 'reported', 'seven', 'further', 'deaths', 'within', 'positive', 'covid', 'wednesday', 'taking', 'total', 'death', 'measure', 'british', 'adult', 'population', 'received', 'doses', 'covid', 'vaccine', 'received', 'least', 'reporting', 'david', 'milliken', 'editing', 'holton', 'newspaper']
['drugs', 'wrongly', 'touted', 'covid', 'treatmentsby', 'australian', 'associated', 'presspublished', 'august', 'updated', 'august', '2020medicines', 'falsely', 'touted', 'covid', 'treatments', 'hydroxychloroquine', 'treat', 'malaria', 'rheumatoid', 'arthritis', 'lupus', 'there', 'reliable', 'evidence', 'prevent', 'treat', 'covid', 'studies', 'found', 'things', 'worse', 'remdesivir', 'antiviral', 'medicine', 'people', 'hospital', 'severe', 'covid', 'recover', 'faster', 'people', 'milder', 'covid', 'dexamethasone', 'reduces', 'inflammation', 'treat', 'asthma', 'arthritis', 'reduces', 'dying', 'people', 'hospital', 'serious', 'covid', 'breathe', 'doesn', 'people', 'severe', 'covid', 'could', 'things', 'worse', 'ephedra', 'vitamin', 'other', 'complementary', 'medicines', 'found', 'effective', 'against', 'covid', 'outside', 'intensive', 'source', 'medicinewisenew', 'newspaper']
['covid', 'schools', 'study', 'breakdownby', 'australian', 'associated', 'presspublished', 'april', 'updated', 'april', '2020what', 'national', 'centre', 'immunisation', 'research', 'surveillance', 'ncirs', 'study', 'covid', 'schools', 'found', 'total', 'students', 'staff', 'members', 'schools', 'march', 'april', 'diagnosed', 'covid', 'people', 'students', 'staff', 'members', 'those', 'people', 'total', 'close', 'contacts', 'within', 'school', 'period', 'close', 'contacts', 'people', 'caught', 'covid', 'those', 'people', 'students', 'disease', 'others', 'students', 'passed', 'coronavirus', 'school', 'staff', 'members', 'spread', 'covid', 'within', 'schools', 'limited', 'virus', 'transmission', 'children', 'schools', 'influenza', 'newspaper']
['sydney', 'repeat', 'covid', 'breachesby', 'australian', 'associated', 'presspublished', 'october', 'updated', 'october', '2020the', 'sydney', 'portugal', 'community', 'being', 'forced', 'seven', 'after', 'failing', 'comply', 'covid', 'regulations', 'after', 'three', 'warnings', 'liquor', 'gaming', 'director', 'compliance', 'dimitri', 'argeres', 'portugal', 'marrickville', 'fourth', 'business', 'closed', 'covid', 'safety', 'breaches', 'close', 'wednesday', 'inspectors', 'visited', 'three', 'times', 'observed', 'breaches', 'relating', 'their', 'covid', 'safety', 'overbooking', 'groups', 'gaming', 'machine', 'spacing', 'inadequate', 'check', 'processes', 'argeres', 'tuesday', 'since', 'closure', 'order', 'issued', 'however', 'things', 'fined', 'longer', 'breaches', 'example', 'bookings', 'people', 'rather', 'while', 'guests', 'spaced', 'least', 'metres', 'apart', 'gaming', 'machines', 'changed', 'having', 'robust', 'digital', 'check', 'processes', 'allow', 'effective', 'contact', 'tracing', 'event', 'positive', 'visited', 'venue', 'argeres', 'service', 'covid', 'check', 'businesses', 'registered', 'covid', 'anyone', 'check', 'using', 'service', 'account', 'inspectors', 'liquor', 'gaming', 'trading', 'safework', 'conducted', 'covid', 'safety', 'visits', 'issued', 'penalties', 'worth', 'temporarily', 'closed', 'businesses', 'newspaper']
['tests', 'underway', 'covid', 'treatmentby', 'australian', 'associated', 'presspublished', 'august', 'updated', 'august', '2020australian', 'researchers', 'testing', 'treatment', 'coronavirus', 'provide', 'relief', 'those', 'infected', 'covid', 'limit', 'spread', 'professor', 'david', 'morris', 'international', 'adapted', 'cancer', 'treatment', 'known', 'bromac', 'could', 'prevent', 'virus', 'moving', 'lungs', 'carriers', 'spreading', 'other', 'people', 'trial', 'coronavirus', 'patients', 'being', 'established', 'melbourne', 'hospital', 'could', 'start', 'month', 'bromac', 'under', 'development', 'years', 'cancer', 'treatment', 'includes', 'components', 'together', 'dissolve', 'spike', 'covid', 'rendering', 'unable', 'infect', 'other', 'cells', 'agents', 'pineapple', 'enzyme', 'tested', 'after', 'observed', 'eating', 'pineapples', 'resistant', 'particular', 'gastro', 'conditions', 'taken', 'development', 'decade', 'asked', 'whether', 'adapted', 'treating', 'people', 'infected', 'covid', 'professor', 'david', 'morris', 'statement', 'monday', 'results', 'renders', 'covid', 'spike', 'ineffective', 'stopping', 'infecting', 'other', 'cells', 'results', 'treatment', 'confine', 'covid', 'throat', 'prevent', 'infection', 'infected', 'patients', 'passing', 'virus', 'hoped', 'infected', 'person', 'could', 'medication', 'first', 'signs', 'covid', 'virus', 'tracks', 'could', 'provide', 'effective', 'saving', 'lives', 'protecting', 'vulnerable', 'workers', 'preventing', 'hospitalisation', 'getting', 'people', 'infected', 'covid', 'returning', 'their', 'everyday', 'lives', 'researchers', 'stress', 'treatment', 'vaccine', 'covid', 'could', 'tandem', 'treatment', 'prevention', 'measure']

# LSA Model
number_of_topics=1
words=word_count
model=create_gensim_lsa_model(clean_text,number_of_topics,words)
words_from_non_science = dict(model.show_topic(0, topn=words))#dict and encoding matrix values

dict(model.show_topic(0,topn=5))

{'test': 0.5525012615032754,
 'peopl': 0.32711032908806614,
 'covid': 0.32350304714824646,
 'symptom': 0.2014729774269745,
 'travel': 0.15909033106510684}

from wordcloud import WordCloud
text = dict(model.show_topic(0, topn=20))
l=list(text.keys())
wordcloud = WordCloud(width=150, height=200,max_font_size=25, max_words=20, background_color="white").generate(" ".join(l))
plt.imshow(wordcloud, interpolation='bilinear')
plt.axis("off")
plt.savefig('graph13.png')

# LSA Model
number_of_topics = 20 #
words = word_count
model = create_gensim_lsa_model(clean_text,number_of_topics,words)

a=pd.DataFrame()

for i in range(number_of_topics):
    words_non_science =dict(model.show_topic(i, topn=words))
    b=pd.DataFrame(words_non_science,index=[i])
    a=a.append(b)

a=a.transpose()

top_words = dict(model.show_topic(0,topn=5))

df = pd.DataFrame(columns=list(top_words.keys()), 
                  index = list(top_words.keys()))

l = list(top_words.keys())
print('cosine-similarity')
for i in l:
    for j in l:
            matrix=np.array([a.loc[i],a.loc[j]])
            n = s.metrics.pairwise.cosine_similarity(matrix, matrix, dense_output=True)
            df.loc[[i],[j]] = n[0,1]
print(df)

dfi.export(df, 'df_styled16.png')

cosine-similarity
              test     peopl      covid    symptom     travel
test             1  0.336661  0.0349857   0.898669   0.716668
peopl     0.336661         1   0.308412   0.423709   0.271003
covid    0.0349857  0.308412          1 -0.0604921 -0.0986359
symptom   0.898669  0.423709 -0.0604921          1   0.755495
travel    0.716668  0.271003 -0.0986359   0.755495          1

covid-psychology.txt

document_list,titles,word_count=load_data("","covid-psychology.txt",'NEW PAPER')

Number of words in text file : 86550
Total Number of Documents: 20

clean_text=preprocess_data(document_list)

['international', 'sociology2021', 'author', '2020article', 'reuse', 'guidelines', 'sagepub', 'journals', 'permissionsdoi', '0268580920948807journals', 'sagepub', 'isspsychology', 'politics', 'ofcovid', 'misinfodemics', 'peoplebelieve', 'misinfodemics', 'sonia', 'mukhtaruniversity', 'management', 'technology', 'lahore', 'pakistanabstractmisinfodemics', 'related', 'covid', 'negatively', 'impacted', 'people', 'lives', 'adversehealth', 'psycho', 'sociopolitical', 'outcomes', 'scientific', 'community', 'seeks', 'communicateevidence', 'based', 'information', 'regarding', 'misplaced', 'preventive', 'strategies', 'misinformed', 'helpseeking', 'behaviors', 'global', 'multifaceted', 'systems', 'secondary', 'emerged', 'effects', 'ofmisinfodemics', 'public', 'published', 'articles', 'pubmed', 'embase', 'google', 'scholar', 'elsevierabout', 'covid', 'related', 'misinfodemics', 'considered', 'reviewed', 'article', 'thisreview', 'examines', 'mechanisms', 'operational', 'structure', 'prevalence', 'predictive', 'factors', 'effects', 'responses', 'potential', 'curtailing', 'strategies', 'misinfodemics', 'covid', 'present', 'articleshows', 'popular', 'variants', 'covid', 'misinfodemics', 'could', 'joint', 'product', 'apsychological', 'predisposition', 'which', 'either', 'reject', 'information', 'experts', 'perceive', 'thecrisis', 'situation', 'product', 'misinfodemics', 'mechanisms', 'partisan', 'ideological', 'motivations', 'psychological', 'foundations', 'political', 'disposition', 'misinfodemics', 'implications', 'thedevelopment', 'strategies', 'designed', 'curtail', 'negative', 'consequences', 'public', 'health', 'keywordsconspiracy', 'theories', 'covid', 'health', 'communication', 'misinformation', 'mistrust', 'sciencethe', 'mechanisms', 'misinfodemicsin', 'modern', 'mainstream', 'social', 'media', 'become', 'primary', 'source', 'information', 'people', 'around', 'world', 'misinfodemics', 'surroundingcorresponding', 'author', 'sonia', 'mukhtar', 'university', 'management', 'technology', 'block', 'phase', 'johar', 'lahore', 'punjab', '54770', 'pakistan', 'email', 'sonia', 'mukhtar12', 'gmail', 'com948807iss0010', '0268580920948807international', 'sociologymukhtarresearch', 'article2020article112', 'international', 'sociology', 'covid', 'pandemic', 'challenging', 'ongoing', 'coronavirus', 'covid', 'pandemic', 'outbreak', 'highlighted', 'interconnectedness', 'modernglobalized', 'world', 'where', 'public', 'health', 'threats', 'extend', 'beyond', 'their', 'point', 'origindue', 'unvarying', 'reliance', 'misplaced', 'confidence', 'media', 'platforms', 'duringlockdown', 'quarantine', 'isolation', 'social', 'distancing', 'virtual', 'communication', 'hasbecome', 'major', 'source', 'interaction', 'holman', 'covid', 'pandemic', 'outbreak', 'escalated', 'challenges', 'forhealthcare', 'social', 'educational', 'economic', 'political', 'environmental', 'cultural', 'socioeconomic', 'systems', 'world', 'gained', 'momentum', 'innumerablemisinfodemics', 'mechanisms', 'rumors', 'myths', 'superstitions', 'conspiracy', 'theories', 'claims', 'hoaxes', 'false', 'misinformation', 'polarization', 'mistrust', 'science', 'intimes', 'crisis', 'absence', 'checking', 'misinformation', 'misleading', 'content', 'falsecontext', 'manipulated', 'fabricated', 'material', 'imposter', 'documents', 'disinformation', 'regarding', 'etiology', 'outcomes', 'misplaced', 'prevention', 'disease', 'mukhtar', '2020a', 'covid', 'pandemic', 'outbreak', 'saturated', 'mainstream', 'media', 'which', 'disseminate', 'information', 'local', 'global', 'scale', 'similarly', 'social', 'media', 'platforms', 'havealso', 'become', 'accessible', 'source', 'information', 'numerous', 'incidents', 'initiated', 'bythese', 'rumors', 'caused', 'several', 'mishaps', 'across', 'world', 'instance', 'hisown', 'after', 'positive', 'diagnosis', 'covid', 'india', 'people', 'overdosed', 'onthe', 'cholorquine', 'after', 'about', 'effectiveness', 'against', 'covid', 'proliferated', 'nigeria', 'busari', 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'thematic', 'coding', 'categorizing', 'analyzing', 'qualitative', 'london', 'pages', 'french', 'gergle', 'oberlander', 'language', 'emotion', 'short', 'texts', 'proceedingsof', 'conference', 'computer', 'supported', 'cooperative', 'pages', 'goffman', 'stigma', 'notes', 'management', 'spoiled', 'identity', 'simon', 'schuster', 'gonzalez', 'hidalgo', 'barabasi', 'understanding', 'individual', 'human', 'mobility', 'patterns', 'nature', 'graham', 'haidt', 'nosek', 'liberals', 'conservatives', 'different', 'moral', 'foundations', 'journal', 'personality', 'social', 'psychology', 'graham', 'haidt', 'koleva', 'motyl', 'wojcik', 'ditto', 'moral', 'foundations', 'theory', 'thepragmatic', 'validity', 'moral', 'pluralism', 'advances', 'experimental', 'social', 'psychology', 'volume', 'pages', 'elsevier', 'grossman', 'rexer', 'thirumurthy', 'political', 'partisanship', 'influences', 'behavioral', 'responses', 'togovernors', 'recommendations', 'covid', 'prevention', 'united', 'states', 'available', '3578695', 'hebert', 'clemow', 'pbert', 'ockene', 'ockene', 'social', 'desirability', 'dietary', 'report', 'maycompromise', 'validity', 'dietary', 'intake', 'measures', 'international', 'journal', 'epidemiology', 'hochreiter', 'schmidhuber', 'short', 'memory', 'neural', 'computation', 'hofstede', 'hofstede', 'minkov', 'cultures', 'organizations', 'software', 'volume', 'mcgraw', 'holmes', 'connor', 'perry', 'tracey', 'wessely', 'arseneault', 'ballard', 'christensen', 'silver', 'everall', 'multidisciplinary', 'research', 'priorities', 'covid', 'pandemic', 'action', 'mentalhealth', 'science', 'lancet', 'psychiatry', 'jiang', 'assessment', 'public', 'attention', 'perception', 'emotional', 'andbehavioural', 'responses', 'covid', 'outbreak', 'social', 'media', 'surveillance', 'china', 'perception', 'emotionaland', 'behavioural', 'responses', 'covid', 'outbreak', 'social', 'media', 'surveillance', 'china', 'huang', 'bidirectional', 'models', 'sequence', 'tagging', 'arxiv', 'preprint', 'arxiv', '01991', 'auriemma', 'cashaw', 'report', 'underreporting', 'depression', 'journal', 'ofpersonality', 'assessment', 'epidemic', 'psychology', 'works', 'twitter', 'husnayain', 'applications', 'google', 'search', 'trends', 'communication', 'infectiousdisease', 'management', 'study', 'covid', 'outbreak', 'taiwan', 'international', 'journal', 'infectious', 'diseases', 'jimeno', 'yepes', 'mackinlay', 'identifying', 'diseases', 'drugs', 'symptoms', 'twitter', 'studies', 'health', 'technology', 'informatics', 'johnson', 'fendrich', 'modeling', 'sources', 'report', 'survey', 'epidemiology', 'annals', 'ofepidemiology', 'tobin', 'massey', 'anderson', 'measuring', 'emotional', 'expression', 'linguisticinquiry', 'count', 'american', 'journal', 'psychology', 'pages', 'huremovi', 'psychology', 'pandemic', 'psychiatry', 'pandemics', 'pages', 'springer', 'kornfield', 'gustafson', 'before', 'relapse', 'howlanguage', 'online', 'discussion', 'forum', 'predicts', 'risky', 'drinking', 'among', 'those', 'recovery', 'healthcommunication', 'kouzy', 'jaoude', 'kraitem', 'karam', 'zarka', 'traboulsi', 'baddour', 'coronavirus', 'viral', 'quantifying', 'covid', 'misinformation', 'epidemic', 'twitter', 'cureus', 'ubler', 'wessler', 'avioli', 'death', 'dying', 'goodchild', 'spatial', 'temporal', 'socioeconomic', 'patterns', 'twitter', 'flickr', 'cartography', 'geographic', 'information', 'science', 'impact', 'covid', 'epidemic', 'declaration', 'psychologicalconsequences', 'study', 'active', 'weibo', 'users', 'international', 'journal', 'environmental', 'research', 'public', 'health', 'liang', 'effect', 'covid', 'youth', 'mental', 'health', 'psychiatric', 'quarterly', 'pages', 'goyal', 'joshi', 'lewis', 'zettlemoyer', 'stoyanov', 'roberta', 'robustly', 'optimized', 'pretraining', 'approach', 'arxiv', 'preprint', 'arxiv', '11692', 'utkepohl', 'introduction', 'multiple', 'series', 'analysis', 'springer', 'science', 'business', 'media', 'maslow', 'theory', 'human', 'motivation', 'psychological', 'review', 'mcconnell', 'banks', 'avian', 'planning', 'possible', 'pandemic', 'trading', 'technology', 'mohammad', 'turney', 'crowdsourcing', 'emotion', 'association', 'lexicon', 'computational', 'intelligence', 'moinet', 'pastor', 'satorras', 'barrat', 'effect', 'perception', 'epidemic', 'spreading', 'temporal', 'networks', 'physical', 'review', '012313', 'connor', 'balasubramanyan', 'routledge', 'smith', 'tweets', 'polls', 'linking', 'sentimentto', 'public', 'opinion', 'series', 'fourth', 'international', 'conference', 'weblogs', 'social', 'media', 'oyeyemi', 'gabarron', 'ebola', 'twitter', 'misinformation', 'dangerous', 'combination', 'g6178', 'painter', 'political', 'beliefs', 'affect', 'compliance', 'covid', 'social', 'distancing', 'orders', 'available', 'ssrn3569098', 'palshikar', 'simple', 'algorithms', 'detection', 'series', 'advanced', 'dataanalysis', 'business', 'analytics', 'intelligence', 'volume', 'paszke', 'gross', 'chintala', 'chanan', 'devito', 'desmaison', 'antiga', 'lerer', 'automatic', 'differentiation', 'pytorch', 'proceedings', 'advances', 'neural', 'information', 'processing', 'systemsautodiff', 'workshop', 'epidemic', 'psychology', 'works', 'twitterj', 'pennington', 'socher', 'manning', 'glove', 'global', 'vectors', 'representation', 'proceedings', 'theconference', 'empirical', 'methods', 'natural', 'language', 'processing', 'pages', 'association', 'computationallinguistics', 'perrin', 'anderson', 'share', 'adults', 'using', 'social', 'media', 'including', 'facebook', 'ismostly', 'unchanged', 'since', 'https', 'pewresearch', 'share', 'adults', 'using', 'social', 'media', 'including', 'facebook', 'mostly', 'unchanged', 'since', 'plutchik', 'emotions', 'university', 'press', 'america', 'pulido', 'villarejo', 'carballido', 'redondo', 'covid', 'infodemic', 'retweetsfor', 'science', 'based', 'information', 'coronavirus', 'false', 'information', 'international', 'sociology', 'page0268580920914755', 'nationwide', 'survey', 'psychological', 'distress', 'among', 'chinesepeople', 'covid', 'epidemic', 'implications', 'policy', 'recommendations', 'general', 'psychiatry', 'rezapour', 'diesner', 'enhancing', 'measurement', 'social', 'effects', 'capturing', 'morality', 'inproceedings', 'tenth', 'workshop', 'computational', 'approaches', 'subjectivity', 'sentiment', 'social', 'mediaanalysis', 'pages', 'russell', 'mining', 'social', 'mining', 'facebook', 'twitter', 'linkedin', 'google', 'github', 'reilly', 'media', 'alani', 'alleviating', 'sparsity', 'twitter', 'sentiment', 'analysis', 'workshop', 'proceedings', 'salathe', 'bengtsson', 'bodnar', 'brewer', 'brownstein', 'buckee', 'campbell', 'cattuto', 'khandelwal', 'mabry', 'digital', 'epidemiology', 'comput', 'e1002616', 'scepanovic', 'martin', 'lopez', 'quercia', 'baykaner', 'extracting', 'medical', 'entities', 'social', 'media', 'inproceedings', 'conference', 'health', 'inference', 'learning', 'pages', 'schutz', 'luckmann', 'zaner', 'engelhardt', 'structures', 'world', 'number', 'northwest', 'university', 'studies', 'phenomenology', 'existential', 'philosophy', 'northwestern', 'university', 'press', 'isbn9780810106222', 'https', 'books', 'google', 'books', 'lgxbxi0xsh8c', 'gustafson', 'hawkins', 'cleary', 'mctavish', 'pingree', 'eliason', 'lumpkins', 'effects', 'prayer', 'religious', 'expression', 'within', 'computer', 'support', 'groups', 'women', 'breastcancer', 'psycho', 'oncology', 'journal', 'psychological', 'social', 'behavioral', 'dimensions', 'cancer', 'rudzicz', 'detecting', 'anxiety', 'through', 'reddit', 'proceedings', 'fourth', 'workshop', 'compu', 'tational', 'linguistics', 'clinical', 'psychology', 'linguistic', 'signal', 'clinical', 'reality', 'pages', 'shultz', 'baingana', 'neria', 'ebola', 'outbreak', 'mental', 'health', 'current', 'status', 'recom', 'mended', 'response', 'simms', 'ramstedt', 'richards', 'martinez', 'giraud', 'carrier', 'detecting', 'cognitive', 'distortionsthrough', 'machine', 'learning', 'analytics', 'international', 'conference', 'healthcare', 'informatics', 'pages', 'smith', 'shinebourne', 'interpretative', 'phenomenological', 'analysis', 'american', 'psychological', 'association', 'sommariva', 'vamos', 'mantzarlis', 'martinez', 'tyson', 'spreading', 'exploringhealth', 'messages', 'social', 'media', 'implications', 'health', 'professionals', 'using', 'study', 'american', 'journalof', 'health', 'education', 'strong', 'epidemic', 'psychology', 'model', 'sociology', 'health', 'illness', 'tajfel', 'turner', 'austin', 'worchel', 'integrative', 'theory', 'intergroup', 'conflict', 'organizationalidentity', 'tausczik', 'pennebaker', 'psychological', 'meaning', 'words', 'computerized', 'analysismethods', 'journal', 'language', 'social', 'psychology', 'epidemic', 'psychology', 'works', 'twitter', '21the', 'economist', 'millions', 'stuck', 'online', 'wellness', 'dustry', 'booming', 'https', 'economist', 'international', 'millions', 'stuck', 'online', 'wellness', 'industry', 'booming', 'bavel', 'baicker', 'boggio', 'capraro', 'cichocka', 'cikara', 'crockett', 'douglas', 'druckman', 'using', 'social', 'behavioural', 'science', 'support', 'covid', 'pandemic', 'response', 'nature', 'human', 'behaviour', 'pages', 'varol', 'ferrara', 'davis', 'menczer', 'flammini', 'online', 'human', 'interactions', 'detection', 'estimation', 'characterization', 'eleventh', 'international', 'conference', 'social', 'media', 'immediate', 'psychological', 'responses', 'associatedfactors', 'during', 'initial', 'stage', 'coronavirus', 'disease', 'covid', 'epidemic', 'among', 'general', 'populationin', 'china', 'international', 'journal', 'environmental', 'research', 'public', 'health', 'waterloo', 'baumgartner', 'peter', 'valkenburg', 'norms', 'online', 'expressions', 'emotion', 'comparing', 'facebook', 'twitter', 'instagram', 'whatsapp', 'media', 'society', 'windsor', 'dowell', 'graesser', 'language', 'autocrats', 'leaders', 'language', 'natural', 'disaster', 'crises', 'hazards', 'crisis', 'public', 'policy', 'wojcik', 'hughes', 'sizing', 'twitter', 'users', 'washington', 'research', 'center', 'theis', 'kordy', 'language', 'eating', 'disorder', 'blogs', 'psychological', 'implications', 'social', 'onlineactivity', 'journal', 'language', 'social', 'psychology', 'propagating', 'debunking', 'conspiracy', 'theories', 'twitter', 'during', 'virus', 'outbreak', 'cyberpsychology', 'behavior', 'social', 'networking', 'torres', 'menczer', 'prevalence', 'credibility', 'information', 'twitter', 'during', 'thecovid', 'outbreak', 'arxiv', 'preprint', 'arxiv', '14484', 'acknowledgmentswe', 'thank', 'sarah', 'konrath', 'rosta', 'farzan', 'licia', 'capra', 'their', 'useful', 'feedback', 'manuscript', 'researchwas', 'partly', 'supported', 'grant', 'green', 'routes', '869764', 'availabilitythe', 'daily', 'aggregates', 'measurements', 'available', 'https', 'figshare', '14892642', 'tweet', 'available', 'https', 'github', 'echen102', 'covid', 'tweetids', 'other', 'datasetsand', 'visualizations', 'available', 'project', 'social', 'dynamics', 'epidemicpsychology', 'competing', 'intereststhe', 'author', 'declare', 'competing', 'interests', 'epidemic', 'psychology', 'works', 'twittersupplementary', 'materialsspatial', 'representativeness', 'twitter', 'geographical', 'penetration', 'twitterdata', 'reflects', 'spatial', 'distribution', 'population', 'compared', 'activity', 'state', 'withthe', 'census', 'population', 'figure', 'shows', 'number', 'twitter', 'users', 'volume', 'their', 'tweetscorrelate', 'strongly', 'census', 'population', 'population', 'estimates', 'level', 'states', 'https', 'census', '17log', 'population', '1213141516log', 'tweets', '08814', '17log', 'population', '91011121314log', 'users', '106figure', 'correlation', 'census', 'population', 'states', 'estimated', 'thenumber', 'tweets', 'posted', 'those', 'states', 'number', 'unique', 'twitter', 'users', 'postedat', 'least', 'tweet', 'right', 'during', 'period', 'analysis', 'linear', 'shown', 'together', 'thecoefficient', 'determination', 'linear', 'regression', 'pearson', 'correlation', 'coefficient', 'andthe', 'coefficient', 'number', 'tweets', 'twitter', 'users', 'scale', 'almost', 'linearlywith', 'population', 'estimates', 'signals', 'racism', 'twitter', 'discussions', 'corroborate', 'qualitative', 'intuition', 'first', 'phase', 'wascharacterized', 'discussions', 'depicted', 'pandemic', 'foreign', 'problem', 'often', 'using', 'racist', 'undertones', 'wemeasured', 'volume', 'tweets', 'containing', 'hashtags', 'clear', 'indicators', 'content', 'either', 'racist', 'oraimed', 'antagonizing', 'china', 'manually', 'selected', 'those', 'hashtags', 'hashtags', 'appeared', 'atleast', 'times', 'dataset', 'figure', 'shows', 'normalized', 'volume', 'those', 'hashtags', 'theypeak', 'during', 'first', 'phase', 'related', 'mentions', 'focus', 'twitter', 'discussions', 'china', 'asianforeigners', 'their', 'peaks', 'breakdown', 'phases', 'state', 'during', 'period', 'analysis', 'country', 'fragmented', 'regions', 'thatwere', 'dealing', 'different', 'stages', 'outbreak', 'policies', 'contrast', 'varied', 'across', 'states', 'assesswhether', 'those', 'differences', 'impacted', 'unfolding', 'psycho', 'social', 'epidemics', 'across', 'states', 'computed', 'themeasures', 'represent', 'relative', 'presence', 'three', 'phases', 'refusal', 'anger', 'acceptance', 'state', 'individually', 'results', 'shown', 'figure', 'despite', 'minor', 'differences', 'state', 'level', 'curvesindicate', 'three', 'phases', 'place', 'states', 'sequence', 'phases', 'consistent', 'across', 'states', 'refusal', 'followed', 'anger', 'which', 'followed', 'acceptance', 'there', 'little', 'variation', 'thetimes', 'transition', 'between', 'phases', 'epidemic', 'psychology', 'works', 'twitter']

# LSA Model
number_of_topics=1
words=word_count
model=create_gensim_lsa_model(clean_text,number_of_topics,words)
words_from_psychology =dict(model.show_topic(0, topn=words))#dict and encoding matrix values

dict(model.show_topic(0,topn=5))

{'covid': 0.3733564956223995,
 'psycholog': 0.26785991090419725,
 'social': 0.2517797817165566,
 'epidem': 0.19223792506781598,
 'health': 0.18194229083665533}

from wordcloud import WordCloud
text = dict(model.show_topic(0, topn=20))
l=list(text.keys())
wordcloud = WordCloud(width=150, height=200,max_font_size=25, max_words=20, background_color="white").generate(" ".join(l))
plt.imshow(wordcloud, interpolation='bilinear')
plt.axis("off")
plt.savefig('graph14.png')

# LSA Model
number_of_topics = 20 #
words = word_count
model = create_gensim_lsa_model(clean_text,number_of_topics,words)

a=pd.DataFrame()

for i in range(number_of_topics):
    words_psychology =dict(model.show_topic(i, topn=words))
    b=pd.DataFrame(words_psychology,index=[i])
    a=a.append(b)

a=a.transpose()

top_words = dict(model.show_topic(0,topn=5))

df = pd.DataFrame(columns=list(top_words.keys()), 
                  index = list(top_words.keys()))

l = list(top_words.keys())
print('cosine-similarity')
for i in l:
    for j in l:
            matrix=np.array([a.loc[i],a.loc[j]])
            n = s.metrics.pairwise.cosine_similarity(matrix, matrix, dense_output=True)
            df.loc[[i],[j]] = n[0,1]
print(df)

dfi.export(df, 'df_styled17.png')

cosine-similarity
               covid psycholog     social     epidem     health
covid              1  0.150447  0.0375207 -0.0516623  0.0207802
psycholog   0.150447         1   0.168003   0.125162   0.380477
social     0.0375207  0.168003          1    0.44382  0.0839178
epidem    -0.0516623  0.125162    0.44382          1  0.0126691
health     0.0207802  0.380477  0.0839178  0.0126691          1

2. 2-3 paragraphs

covid-science.txt

def load_data(path,file_name):
    """
    Input  : path and file_name
    Purpose: loading text file
    Output : list of paragraphs/documents and
             title(initial 100 words considred as title of document)
    """
    documents_list = []
    titles=[]
    document = ''
    i=0
    with open( os.path.join(path, file_name) ,"r",encoding="utf8") as fin:
        data = fin.read()
        words = data.split()
        fin.seek(0)
        print('Number of words in text file :', len(words))
        for word in words:
                i=i+1
                document = document+word+' '
                if i == 200:
                    documents_list.append(document)
                    document,i = '',0
                    if len(documents_list) == 2:
                        break
    print("Total Number of Documents:",len(documents_list))
    #titles.append( text[0:min(len(text),100)] )
    return documents_list,titles,len(words)

document_list,titles,word_count=load_data("","covid-science.txt")

Number of words in text file : 120257
Total Number of Documents: 2

clean_text=preprocess_data(document_list)

['covidgr', 'dataset', 'covid', 'sdnet', 'methodology', 'predicting', 'covid', 'based', 'chest', 'images', 'tabik', 'gómez', 'martín', 'rodríguez', 'sevillano', 'garcía', 'charte', 'guirado', 'suárez', 'luengo', 'valero', 'gonzález', 'garcía', 'villanova', 'olmedo', 'sánchez', 'herrera', 'abstract', 'currently', 'coronavirus', 'disease', 'covid', 'infectious', 'diseases', 'century', 'diagnosed', 'using', 'testing', 'scans', 'chest', 'images', 'computed', 'tomography', 'scanners', 'testing', 'available', 'medical', 'centers', 'hence', 'cases', 'images', 'become', 'effective', 'assisting', 'clinicians', 'making', 'decisions', 'learning', 'neural', 'networks', 'great', 'potential', 'building', 'covid', 'triage', 'systems', 'detecting', 'covid', 'patients', 'especially', 'patients', 'severity', 'unfortunately', 'current', 'databases', 'allow', 'building', 'systems', 'highly', 'heterogeneous', 'biased', 'towards', 'severe', 'cases', 'article', 'threefold', 'demystify', 'sensitivities', 'achieved', 'recent', 'covid', 'classification', 'models', 'under', 'close', 'collaboration', 'hospital', 'universitario', 'clínico', 'cecilio', 'granada', 'spain', 'built', 'covidgr', 'homogeneous', 'balanced', 'database', 'includes', 'levels', 'manuscript', 'received', 'september', 'revised', 'october', 'accepted', 'november']
['publication', 'november', 'current', 'version', 'december', 'supported', 'project', 'deepscop', 'ayudas', 'fundación', 'equipos', 'investigación', 'científica', 'covid19_rx', 'ayudas', 'fundación', 'equipos', 'investigación', 'científica', 'covid', 'spanish', 'ministry', 'science', 'technology', 'under', 'project', 'tin2017', '89517', 'tabik', 'supported', 'ramon', 'cajal', 'programme', '18136', 'gómez', 'supported', 'programme', 'fpu16', '04765', 'charte', 'supported', 'programme', 'fpu17', '04069', 'suárez', 'supported', 'programme', 'fpu18', '05989', 'supported', 'european', 'research', 'council', 'grant', 'agreement', '647038', 'biodesert', 'project', 'approved', 'provincial', 'research', 'ethics', 'committee', 'granada', 'corresponding', 'author', 'siham', 'tabik', 'tabik', 'gómez', 'sevillano', 'garcía', 'charte', 'suárez', 'luengo', 'herrera', 'andalusian', 'research', 'institute', 'science', 'computational', 'intelligence', 'university', 'granada', '18071', 'granada', 'spain', 'siham', 'anabelgrios', 'decsai', 'isega24ivan', 'gmail', 'fdavidcl', 'jlsuarezdiaz', 'julianlm', 'decsai', 'herrera', 'decsai', 'martín', 'rodríguez', 'valero', 'gonzález', 'garcía', 'villanova', 'olmedo', 'sánchez', 'hospital', 'universitario', 'clínico', 'cecilio', 'granada', '36310', 'spain', 'joseluismartin', 'hotmail', 'valerogonzalez', 'yahoo', 'pgvillanova', 'gmail', 'euolm', 'yahoo', 'atlanttic', 'research', 'center']

# LSA Model
number_of_topics=1
words=word_count
model=create_gensim_lsa_model(clean_text,number_of_topics,words)
words_from_science=dict(model.show_topic(0, topn=words))##dict and encoding matrix values

dict(model.show_topic(0, topn=5))

{'support': 0.3289947178827898,
 'granada': 0.24814037209037257,
 'covid': 0.22769581399154248,
 'programm': 0.21932981192185977,
 'research': 0.21932981192185977}

from wordcloud import WordCloud
text = dict(model.show_topic(0, topn=20))
l=list(text.keys())
wordcloud = WordCloud(width=150, height=200,max_font_size=25, max_words=20, background_color="white").generate(" ".join(l))
plt.imshow(wordcloud, interpolation='bilinear')
plt.axis("off")
plt.savefig('graph15.png')

# LSA Model
number_of_topics = 2 #
words = word_count
model = create_gensim_lsa_model(clean_text,number_of_topics,words)

a=pd.DataFrame()

for i in range(number_of_topics):
    words_science =dict(model.show_topic(i, topn=words))
    b=pd.DataFrame(words_science,index=[i])
    a=a.append(b)

a=a.transpose()

top_words = dict(model.show_topic(0,topn=5))

df = pd.DataFrame(columns=list(top_words.keys()), 
                  index = list(top_words.keys()))

l = list(top_words.keys())
print('cosine-similarity')
for i in l:
    for j in l:
            matrix=np.array([a.loc[i],a.loc[j]])
            n = s.metrics.pairwise.cosine_similarity(matrix, matrix, dense_output=True)
            df.loc[[i],[j]] = n[0,1]
print(df)

dfi.export(df, 'df_styled18.png')

cosine-similarity
            support   granada      covid   programm   research
support           1  0.956969 -0.0794645          1          1
granada    0.956969         1   0.213226   0.956969   0.956969
covid    -0.0794645  0.213226          1 -0.0794645 -0.0794645
programm          1  0.956969 -0.0794645          1          1
research          1  0.956969 -0.0794645          1          1

covid-non-science.txt

document_list,titles,word_count=load_data("","covid-non-science.txt")

Number of words in text file : 8713
Total Number of Documents: 2

clean_text=preprocess_data(document_list)

['covid', 'recovery', 'covid', 'reality', 'reuters', 'published', 'updated', 'jones', 'london', 'reuters', 'world', 'shares', 'inched', 'towards', 'month', 'friday', 'industrial', 'bellwether', 'metal', 'copper', 'longest', 'weekly', 'winning', 'streak', 'nearly', 'three', 'years', 'recovering', 'global', 'nagging', 'coronavirus', 'nerves', 'market', 'rally', 'fuelled', 'record', 'numbers', 'largely', 'blown', 'itself', 'spike', 'covid', 'cases', 'though', 'fastest', 'expansion', 'china', 'services', 'sector', 'decade', 'stimulus', 'ensured', 'optimism', 'remained', 'chinese', 'shares', 'charged', 'their', 'highest', 'level', 'years', 'helping', 'asian', 'indexes', 'month', 'peaks', 'sight', 'european', 'markets', 'stalling', 'early', 'traders', 'surprise', 'currency', 'commodity', 'markets', 'subdued', 'after', 'otherwise', 'strong', 'confidence', 'sensitive', 'stalwarts', 'copper', 'sterling', 'australian', 'dollar', 'which', 'struggled', 'friday', 'think', 'infection', 'rates', 'fears', 'localised', 'lockdowns', 'doused', 'enthusiasm', 'societe', 'generale', 'strategist', 'jukes', 'three', 'elements', 'vaccine', 'hopes', 'decent', 'places', 'return']
['infection', 'rates', 'which', 'nervous', 'against', 'basket', 'currencies', 'dollar', 'slightly', 'early', 'london', 'trading', 'still', 'firmly', 'track', 'biggest', 'weekly', 'since', 'first', 'though', 'gained', 'against', 'swiss', 'franc', 'versus', 'sometimes', 'commodity', 'driven', 'norwegian', 'crown', 'futures', 'volumes', 'lower', 'usual', 'markets', 'holiday', 'friday', 'independence', 'nonfarm', 'payrolls', 'surged', 'million', 'above', 'average', 'forecast', 'million', 'thanks', 'rises', 'hospitality', 'sectors', 'economists', 'noted', 'there', 'caveats', 'upbeat', 'headline', 'figures', 'number', 'permanent', 'losers', 'continued', 'increasing', 'million', 'while', 'unemployment', 'remains', 'chunky', 'percentage', 'points', 'above', 'february', 'level', 'deutsche', 'analysis', 'unemployment', 'behind', 'developed', 'market', 'peers', 'barring', 'canada', 'recovery', 'faces', 'headwinds', 'surge', 'coronavirus', 'infections', 'prompts', 'states', 'delay', 'cases']

# LSA Model
number_of_topics=1
words=word_count
model=create_gensim_lsa_model(clean_text,number_of_topics,words)
words_non_science =dict(model.show_topic(0, topn=words))##dict and encoding matrix values

dict(model.show_topic(0, topn=5))

{'market': 0.2986573559242644,
 'covid': 0.21979867961934102,
 'friday': 0.18596179123202222,
 'infect': 0.15212490284470373,
 'copper': 0.1465324530795617}

from wordcloud import WordCloud
text = dict(model.show_topic(0, topn=20))
l=list(text.keys())
wordcloud = WordCloud(width=150, height=200,max_font_size=25, max_words=20, background_color="white").generate(" ".join(l))
plt.imshow(wordcloud, interpolation='bilinear')
plt.axis("off")
plt.savefig('graph16.png')

# LSA Model
number_of_topics = 2 #
words = word_count
model = create_gensim_lsa_model(clean_text,number_of_topics,words)

a=pd.DataFrame()

for i in range(number_of_topics):
    words_non_science =dict(model.show_topic(i, topn=words))
    b=pd.DataFrame(words_non_science,index=[i])
    a=a.append(b)

a=a.transpose()

top_words = dict(model.show_topic(0,topn=5))

df = pd.DataFrame(columns=list(top_words.keys()), 
                  index = list(top_words.keys()))

l = list(top_words.keys())
print('cosine-similarity')
for i in l:
    for j in l:
            matrix=np.array([a.loc[i],a.loc[j]])
            n = s.metrics.pairwise.cosine_similarity(matrix, matrix, dense_output=True)
            df.loc[[i],[j]] = n[0,1]
print(df)

dfi.export(df, 'df_styled19.png')

cosine-similarity
          market     covid    friday    infect      year
market         1  0.741138  0.986861  0.813347  0.741138
covid   0.741138         1  0.839872  0.212223         1
friday  0.986861  0.839872         1  0.708661  0.839872
infect  0.813347  0.212223  0.708661         1  0.212223
year    0.741138         1  0.839872  0.212223         1

covid-psychology.txt

document_list,titles,word_count=load_data("","covid-psychology.txt")

Number of words in text file : 86550
Total Number of Documents: 2

clean_text=preprocess_data(document_list)

['international', 'sociology', 'author', 'article', 'reuse', 'guidelines', 'sagepub', 'journals', 'permissions', '0268580920948807', 'journals', 'sagepub', 'psychology', 'politics', 'covid', 'misinfodemics', 'people', 'believe', 'misinfodemics', 'sonia', 'mukhtar', 'university', 'management', 'technology', 'lahore', 'pakistan', 'abstract', 'misinfodemics', 'related', 'covid', 'negatively', 'impacted', 'people', 'lives', 'adverse', 'health', 'psycho', 'sociopolitical', 'outcomes', 'scientific', 'community', 'seeks', 'communicate', 'evidence', 'based', 'information', 'regarding', 'misplaced', 'preventive', 'strategies', 'misinformed', 'helpseeking', 'behaviors', 'global', 'multifaceted', 'systems', 'secondary', 'emerged', 'effects', 'misinfodemics', 'public', 'published', 'articles', 'pubmed', 'embase', 'google', 'scholar', 'elsevier', 'about', 'covid', 'related', 'misinfodemics', 'considered', 'reviewed', 'article', 'review', 'examines', 'mechanisms', 'operational', 'structure', 'prevalence', 'predictive', 'factors', 'effects', 'responses', 'potential', 'curtailing', 'strategies', 'misinfodemics', 'covid', 'present', 'article', 'shows', 'popular', 'variants', 'covid', 'misinfodemics', 'could', 'joint', 'product', 'psychological', 'predisposition', 'which', 'either', 'reject', 'information', 'experts', 'perceive', 'crisis', 'situation', 'product', 'misinfodemics', 'mechanisms', 'partisan', 'ideological', 'motivations', 'psychological', 'foundations', 'political', 'disposition', 'misinfodemics', 'implications', 'development', 'strategies', 'designed', 'curtail', 'negative', 'consequences', 'public', 'health', 'keywords', 'conspiracy', 'theories', 'covid']
['health', 'communication', 'misinformation', 'mistrust', 'science', 'mechanisms', 'misinfodemics', 'modern', 'mainstream', 'social', 'media', 'become', 'primary', 'source', 'information', 'people', 'around', 'world', 'misinfodemics', 'surrounding', 'corresponding', 'author', 'sonia', 'mukhtar', 'university', 'management', 'technology', 'block', 'phase', 'johar', 'lahore', 'punjab', '54770', 'pakistan', 'email', 'sonia', 'mukhtar12', 'gmail', '948807iss0010', '0268580920948807international', 'sociologymukhtar', 'research', 'article2020', 'article', 'international', 'sociology', 'covid', 'pandemic', 'challenging', 'ongoing', 'coronavirus', 'covid', 'pandemic', 'outbreak', 'highlighted', 'interconnectedness', 'modern', 'globalized', 'world', 'where', 'public', 'health', 'threats', 'extend', 'beyond', 'their', 'point', 'origin', 'unvarying', 'reliance', 'misplaced', 'confidence', 'media', 'platforms', 'during', 'lockdown', 'quarantine', 'isolation', 'social', 'distancing', 'virtual', 'communication', 'become', 'major', 'source', 'interaction', 'holman', 'covid', 'pandemic', 'outbreak', 'escalated', 'challenges', 'healthcare', 'social', 'educational', 'economic', 'political', 'environmental', 'cultural', 'socioeconomic', 'systems', 'world', 'gained', 'momentum', 'innumerable', 'misinfodemics', 'mechanisms', 'rumors', 'myths', 'superstitions', 'conspiracy', 'theories', 'claims', 'hoaxes', 'false', 'misinformation', 'polarization', 'mistrust', 'science', 'times', 'crisis', 'absence', 'checking', 'misinformation', 'misleading', 'content', 'false', 'context', 'manipulated']

# LSA Model
number_of_topics=1
words=word_count
model=create_gensim_lsa_model(clean_text,number_of_topics,words)
words_from_psychology =dict(model.show_topic(0, topn=words))##dict and encoding matrix values

dict(model.show_topic(0, topn=5))

{'misinfodem': 0.5033743541941371,
 'covid': 0.36297115033235144,
 'articl': 0.21459251935197443,
 'health': 0.14837863098037707,
 'mechan': 0.14837863098037704}

from wordcloud import WordCloud
text = dict(model.show_topic(0, topn=20))
l=list(text.keys())
wordcloud = WordCloud(width=150, height=200,max_font_size=25, max_words=20, background_color="white").generate(" ".join(l))
plt.imshow(wordcloud, interpolation='bilinear')
plt.axis("off")
plt.savefig('graph17.png')

# LSA Model
number_of_topics = 2 #
words = word_count
model = create_gensim_lsa_model(clean_text,number_of_topics,words)

a=pd.DataFrame()

for i in range(number_of_topics):
    words_psychology =dict(model.show_topic(i, topn=words))
    b=pd.DataFrame(words_psychology,index=[i])
    a=a.append(b)

a=a.transpose()

top_words = dict(model.show_topic(0,topn=5))

df = pd.DataFrame(columns=list(top_words.keys()), 
                  index = list(top_words.keys()))

l = list(top_words.keys())
print('cosine-similarity')
for i in l:
    for j in l:
            matrix=np.array([a.loc[i],a.loc[j]])
            n = s.metrics.pairwise.cosine_similarity(matrix, matrix, dense_output=True)
            df.loc[[i],[j]] = n[0,1]
print(df)

dfi.export(df, 'df_styled20.png')

cosine-similarity
           misinfodem     covid    articl    health    mechan
misinfodem          1  0.976353  0.993795  0.755596  0.755596
covid        0.976353         1  0.946251  0.879335  0.879335
articl       0.993795  0.946251         1  0.678051  0.678051
health       0.755596  0.879335  0.678051         1         1
mechan       0.755596  0.879335  0.678051         1         1

Paragraph level

covid-science.txt

def load_data(path,file_name):
    """
    Input  : path and file_name
    Purpose: loading text file
    Output : list of paragraphs/documents and
             title(initial 100 words considred as title of document)
    """
    documents_list = []
    titles=[]
    with open( os.path.join(path, file_name) ,"r",encoding='UTF8') as fin:
        data = fin.read()
        words = data.split()
        fin.seek(0)
        print('Number of words in text file :', len(words))
        for line in fin.readlines():
            text = line.strip()
            if text !='':
                documents_list.append(text)
    print("Total Number of Documents:",len(documents_list))
    titles.append( text[0:min(len(text),100)] )
    return documents_list,titles,len(words)

document_list,titles,word_count=load_data("","covid-science.txt")

Number of words in text file : 120257
Total Number of Documents: 14379

clean_text=preprocess_data(document_list)

['covidgr', 'dataset', 'covid', 'sdnet']
['methodology', 'predicting', 'covid']
['based', 'chest', 'images']
['tabik', 'gómez', 'martín', 'rodríguez', 'sevillano', 'garcía', 'charte']
['guirado', 'suárez', 'luengo', 'valero', 'gonzález', 'garcía', 'villanova']
['olmedo', 'sánchez', 'herrera']
['abstract', 'currently', 'coronavirus', 'disease', 'covid']
['infectious', 'diseases', 'century', 'diagnosed', 'using', 'testing', 'scans']
['chest', 'images', 'computed', 'tomography']
['scanners', 'testing', 'available']
['medical', 'centers', 'hence', 'cases', 'images']
['become', 'effective', 'assisting', 'clinicians', 'making', 'decisions', 'learning', 'neural', 'networks']
['great', 'potential', 'building', 'covid', 'triage', 'systems']
['detecting', 'covid', 'patients', 'especially', 'patients']
['severity', 'unfortunately', 'current', 'databases', 'allow']
['building', 'systems', 'highly', 'heterogeneous']
['biased', 'towards', 'severe', 'cases', 'article', 'threefold', 'demystify', 'sensitivities', 'achieved']
['recent', 'covid', 'classification', 'models', 'under']
['close', 'collaboration', 'hospital', 'universitario', 'clínico']
['cecilio', 'granada', 'spain', 'built', 'covidgr', 'homogeneous', 'balanced', 'database', 'includes', 'levels']
['manuscript', 'received', 'september', 'revised', 'october']
['accepted', 'november', 'publication', 'november']
['current', 'version', 'december', 'supported']
['project', 'deepscop', 'ayudas', 'fundación', 'equipos', 'investigación', 'científica', 'covid19_rx', 'ayudas', 'fundación']
['equipos', 'investigación', 'científica', 'covid']
['spanish', 'ministry', 'science', 'technology', 'under']
['project', 'tin2017', '89517', 'tabik', 'supported', 'ramon', 'cajal']
['programme', '18136', 'gómez', 'supported']
['programme', 'fpu16', '04765', 'charte', 'supported']
['programme', 'fpu17', '04069', 'suárez', 'supported', 'programme', 'fpu18', '05989', 'supported', 'european', 'research']
['council', 'grant', 'agreement', '647038', 'biodesert', 'project']
['approved', 'provincial', 'research', 'ethics', 'committee', 'granada']
['corresponding', 'author', 'siham', 'tabik']
['tabik', 'gómez', 'sevillano', 'garcía', 'charte', 'suárez']
['luengo', 'herrera', 'andalusian', 'research', 'institute']
['science', 'computational', 'intelligence', 'university', 'granada']
['18071', 'granada', 'spain', 'siham', 'anabelgrios', 'decsai']
['isega24ivan', 'gmail', 'fdavidcl', 'jlsuarezdiaz']
['julianlm', 'decsai', 'herrera', 'decsai']
['martín', 'rodríguez', 'valero', 'gonzález', 'garcía', 'villanova']
['olmedo', 'sánchez', 'hospital', 'universitario', 'clínico']
['cecilio', 'granada', '36310', 'spain', 'joseluismartin']
['hotmail', 'valerogonzalez', 'yahoo', 'pgvillanova', 'gmail']
['euolm', 'yahoo']
['atlanttic', 'research', 'center', 'telecommunication', 'technologies', 'university', 'galicia', 'spain']
['mreyarea', 'gmail']
['guirado', 'multidisciplinary', 'institute', 'environment']
['studies', 'ramón', 'margalef', 'university', 'alicante', '03690', 'spain']
['geesecillo', 'gmail']
['digital', 'object', 'identifier', '3037127']
['severity', 'normal', 'positive', 'moderate', 'severe', 'covidgr', 'contains', 'positive']
['negative', 'posteroanterior', 'views']
['propose', 'covid', 'smart', 'based', 'network', 'covid', 'sdnet']
['methodology', 'improving', 'generalization', 'capacity']
['covid', 'classification', 'models', 'approach', 'reaches']
['stable', 'results', 'accuracy']
['severe', 'moderate']
['covid', 'severity', 'levels', 'approach', 'could']
['early', 'detection', 'covid', 'covidgr', 'along']
['severity', 'level', 'labels', 'available', 'scientific', 'community', 'through', 'https', 'dasci', 'transferencia']
['covidgr']
['index', 'terms', 'covid', 'convolutional', 'neural', 'networks']
['smart']
['introduction']
[]
['months', 'world', 'witnessing']
['covid', 'pandemic', 'increasingly', 'infecting', 'large']
['people', 'everywhere', 'world', 'trends']
['clear', 'research', 'confirm', 'problem']
['persist', 'until', 'besides', 'prevalence', 'studies', 'conducted']
['several', 'countries', 'reveal', 'proportion', 'population']
['developed', 'antibodies', 'after', 'exposure', 'virus']
['spain', 'means', 'frequently', 'large', 'number', 'patients']
['assessed', 'small', 'intervals', 'number']
['clinicians', 'resources']
['general', 'covid', 'diagnosis', 'carried', 'using', 'least']
['these', 'three', 'tests', 'computed', 'tomography', 'scans', 'based', 'assessment']
['consists', 'analyzing', 'radiographic', 'images', 'different', 'angles', 'needed', 'equipment', 'assessment']
['available', 'hospitals', 'takes']
['minutes', 'patient', 'addition', 'required']
['decontamination']
['reverse', 'transcription', 'polymerase', 'chain', 'reaction', 'rtpcr', 'detects', 'viral', 'sputum']
['online', 'available', 'https', 'english', 'elpais', 'society']
['antibody', 'study', 'shows', 'spaniards', 'contracted', 'coronavirus']
['online', 'available', 'advocacy', 'economics', 'acrposition', 'statements', 'recommendations', 'chest', 'radiography', 'forsuspected', 'covid19', 'infection']
['article', 'access', 'download', 'along', 'rights', 'mining', 'analysis']
['authorized', 'licensed', 'limited', 'university', 'hertfordshire', 'downloaded', 'xplore', 'restrictions', 'apply']
['journal', 'biomedical', 'health', 'informatics', 'december']
['stratification', 'radiological', 'severity', 'covid', 'examples', 'index', 'calculated']
['nasopharyngeal', 'requires', 'specific', 'material']
['equipment', 'which', 'easily', 'accessible', 'takes']
['least', 'hours', 'which', 'desirable', 'positive', 'covid19', 'patients', 'should', 'identified', 'tracked', 'possible', 'studies', 'found', 'results', 'several']
['tests', 'different', 'points', 'patients', 'variable', 'during', 'course', 'illness', 'producing', 'falsenegative', 'authors', 'suggested']
['should', 'combined', 'other', 'clinical', 'tests']
['chest', 'required', 'equipment']
['assessment', 'cumbersome', 'lightweight']
['transportable', 'general', 'resources']
['available', 'required', 'tests']
['addition', 'takes', 'about', 'seconds', 'patient']
['which', 'makes', 'effective']
['assessment', 'tools']
['recent', 'studies', 'provide', 'estimates', 'expert', 'radiologists']
['sensitivity', 'diagnosis', 'covid', 'based', 'scans']
['study', 'patients', 'chest']
['essay', 'performed', 'within', 'reported']
['sensitivity', 'compared', 'sensitivity']
['different', 'study', 'patients']
['years', 'reported', 'sensitivity', 'compared']
['initial', 'according', 'analysis']
['ambulatory', 'patients', 'patients', 'presenting', 'urgent']
['centers', 'confirmed', 'coronavirus', 'disease', 'normal']
['mildly', 'abnormal', 'findings', 'these', 'patients']
['correctly', 'diagnosed', 'expert']
['recent', 'study', 'authors', 'proposed', 'simplifying', 'quantification', 'level', 'severity', 'adapting', 'previously', 'defined']
['radiographic', 'assessment', 'edema', 'score']
['covid', 'score', 'calculated', 'assigning', 'value']
['between', 'depending', 'extent', 'visual']
['features', 'consolidation', 'ground', 'glass', 'opacities']
['parts', 'depicted', 'based', 'score']
['experts', 'identify', 'level', 'severity', 'infection', 'among']
['severity', 'stages', 'normal', 'moderate']
['severe', 'practice', 'patient', 'classified', 'expert', 'radiologist']
['authorized', 'licensed', 'limited', 'university', 'hertfordshire', 'downloaded', 'xplore', 'restrictions', 'apply']
['tabik', 'covidgr', 'dataset', 'covid', 'sdnet', 'methodology', 'predicting', 'covid', 'based', 'chest', 'images']
['normal', 'positive', 'refer', 'these', 'cases']
['normal', 'expert', 'annotation', 'adopted', 'based']
['score']
['automated', 'image', 'analysis', 'learning', 'models']
['great', 'potential', 'optimize', 'images']
['diagnosis', 'covid', 'robust', 'accurate']
['model', 'could', 'serve', 'triage', 'method', 'support']
['medical', 'decision', 'making', 'increasing', 'number', 'recent', 'works']
['claim', 'achieving', 'impressive', 'sensitivities', 'higher']
['expert', 'radiologists', 'these', 'sensitivities']
['covid', 'dataset', 'covid', 'image']
['collection', 'dataset', 'includes', 'small', 'number']
['covid', 'positive', 'cases', 'coming', 'highly', 'heterogeneous']
['sources', 'least', 'countries', 'cases', 'severe', 'patients']
['issue', 'drastically', 'reduces', 'clinical', 'value', 'populate']
['covid', 'healthy', 'classes', 'researchers', 'using']
['images', 'diverse', 'pulmonary', 'disease', 'repositories']
['obtained', 'models', 'clinical', 'value', 'since']
['unable', 'detect', 'patients', 'moderate', 'severity']
['which', 'target', 'clinical', 'triage', 'system']
['situation', 'there', 'still', 'higher', 'quality', 'datasets', 'built']
['under', 'clinical', 'protocol', 'under', 'close', 'collaboration']
['expert', 'radiologists']
['multiple', 'studies', 'proven', 'higher', 'quality', 'ensures']
['higher', 'quality', 'models', 'concept', 'smart', 'refers']
['process', 'converting', 'higher', 'quality']
['higher', 'concentration', 'useful', 'information', 'smart']
['includes', 'processing', 'methods', 'improve', 'value']
['veracity', 'examples', 'these', 'methods', 'include', 'noise']
['elimination', 'augmentation', 'transformation']
['among', 'other', 'techniques']
['designed', 'clinical', 'quality', 'dataset']
['named', 'covidgr', 'includes', 'levels', 'severity']
['normal', 'moderate', 'severe', 'identified', 'these']
['severity', 'levels', 'recent', 'covid', 'radiological', 'study']
['propose', 'covid', 'smart', 'based', 'network']
['covid', 'sdnet', 'methodology', 'combines', 'segmentation', 'dataaugmentation', 'transformations', 'together', 'appropriate', 'convolutional', 'neural', 'network', 'inference']
['contributions', 'paper', 'summarized', 'follows']
['analyze', 'reliability', 'potential', 'limitations']
['covid', 'datasets', 'models']
['perspective', 'provide', 'first', 'public', 'dataset']
['called', 'covidgr', 'quantifies', 'covid', 'terms']
['severity', 'levels', 'normal', 'moderate', 'severe']
['building', 'triage', 'systems', 'clinical']
['value']
['processing', 'perspective', 'combined', 'several']
['methods', 'eliminate', 'irrelevant', 'information']
['input', 'images', 'processing', 'method']
['called', 'segmentation', 'based', 'cropping', 'increase', 'discrimination', 'capacity', 'classification', 'model']
['class', 'inherent', 'transformation', 'method', 'inspired']
['processing', 'perspective', 'proposed']
['inference', 'process', 'fuses', 'predictions']
['transformed', 'classes', 'obtained', 'class', 'inherent', 'transformation', 'method', 'calculate', 'final', 'prediction']
['global', 'perspective', 'designed', 'novel', 'methodology', 'named', 'covid', 'sdnet', 'generalization', 'capacity', 'covid', 'classification', 'based']
['images', 'covid', 'sdnet', 'combines', 'segmentation', 'datatransformation', 'augmentation', 'suitable']
['model', 'together', 'inference', 'approach', 'final']
['prediction']
['experiments', 'demonstrate', 'approach', 'reaches']
['stable', 'results', 'especially', 'moderate', 'severe', 'levels']
['respectively', 'lower', 'accuracies', 'obtained', 'normal', 'severity', 'levels']
['respectively']
['article', 'organized', 'follows', 'review']
['datasets', 'covid', 'classification', 'approaches', 'provided']
['section', 'section', 'describes', 'covidgr', 'built']
['organized', 'approach', 'presented', 'section', 'experiments', 'comparisons', 'results', 'provided', 'section']
['inspection', 'model', 'decision', 'using', 'heatmaps', 'provided']
['section', 'conclusions', 'pointed', 'section']
['related', 'works']
['months', 'known', 'increasing', 'number', 'works']
['exploring', 'potential', 'learning', 'models', 'automating']
['covid', 'diagnosis', 'based', 'images', 'results']
['promising', 'still', 'needs', 'level']
['models', 'design', 'given', 'potential']
['problems', 'several', 'studies', 'include', 'explication', 'methods', 'their']
['models', 'section', 'analyzes', 'advantages', 'limitations']
['current', 'datasets', 'models', 'building', 'automatic', 'covid']
['diagnosis', 'systems', 'without', 'decision', 'explication']
['datasets']
['there', 'exist', 'quality', 'collection']
['images', 'building', 'covid', 'diagnosis', 'systems', 'clinical', 'value', 'currently', 'source', 'covid', 'class']
['covid', 'image', 'collection', 'contains', 'positive']
['negative', 'views', 'these', 'images', 'obtained', 'highly']
['heterogeneous', 'equipment', 'around', 'world', 'another']
['example', 'covid', 'dataset', 'figure', 'covid', 'chest']
['dataset', 'initiative', 'build', 'covid', 'classes']
['studies', 'using', 'multiple', 'public', 'pulmonary']
['disease', 'examples', 'these', 'repositories', 'pneumonia', 'challenge', 'dataset', 'kaggle']
['chestx', 'dataset']
['mimic', 'dataset']
['padchest', 'dataset']
['instance', 'covidx', 'built', 'combining', 'three']
['public', 'datasets', 'covid', 'image', 'collection']
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[]
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[]
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['abdullah', 'mamun', 'bulbul']
[]
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[]
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[]
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['positive', 'confirmed', 'deaths', 'extracted']
['facts', 'cross', 'validated', 'sources', 'hopkins']
['university', 'hospital', 'licensed', 'number', 'critical', 'staff', 'comprehensive', 'specialty', 'accessed']
['definitive', 'healthcare', 'consulting', 'services', 'national']
['provider', 'identifier', 'registry', 'database', 'respectively']
['collected', 'study', 'converted', 'county', 'scale']
['unique', 'identifier', 'county', 'census', 'standard']
['monitor', 'share', 'dynamic', 'heterogeneity', 'infor', 'mation', 'medical', 'resource', 'distribution', 'medical', 'resource']
['deficiency', 'dashboard', 'created', 'based', 'arcgis', 'board', 'analyzing', 'visualizing', 'generated', 'results']
['figure', 'bubble', 'center', 'dashboard']
['represents', 'spatial', 'distribution', 'where']
['circle', 'refers', 'index', 'value', 'lists', 'counties']
['displayed', 'right', 'statistics']
['infection', 'which', 'interactively', 'generated', 'based']
['selected', 'extend', 'indicator']
['charts', 'fraction', 'hospital', 'types', 'medical']
['staff', 'applied', 'display', 'county']
['dashboard', 'track', 'temporal', 'pattern', 'index']
['chart', 'built', 'bottom', 'demonstrate', 'series']
['analysis', 'result', 'selected']
['figure', 'scraped', 'product', 'monitor', 'medical', 'resource']
['deficiency', 'dynamics', 'covid']
['impact', 'social', 'distancing', 'measures']
['covid', 'cases', 'mortality']
['another', 'study', 'impact', 'control', 'policies', 'using']
['covid', 'scraper', 'corresponding', 'policies', 'dataset']
['study', 'authors', 'analyzed', 'series', 'social', 'distancing']
['policies', 'including', 'school', 'closure', 'workplace', 'closure', 'cancel', 'lation', 'public', 'events', 'public', 'information', 'campaigns', 'cancel']
['public', 'transport', 'internal', 'movement', 'restriction', 'travel']
['control', 'implemented', 'combat', 'world', 'pandemic', 'previous', 'studies', 'found', 'social', 'distancing']
['policies', 'effective', 'mitigating', 'covid']
['however', 'these', 'policies', 'negative', 'impacts', 'economic']
['development', 'normal', 'limited', 'understanding']
['effectiveness', 'individual', 'policy', 'posed', 'grand']
['challenges', 'reopening', 'process', 'which', 'stringency']
['social', 'distancing', 'reduced', 'balance', 'health', 'develop', 'study', 'investigating', 'effectiveness', 'seven', 'major']
['social', 'distancing', 'policies', 'covid']
['mortality', 'growth', 'conducted', 'using']
['collected', 'policy', 'shared', 'oxford', 'policy', 'tracker']
['project', 'estimate', 'temporal', 'dynamic', 'impact']
['policies', 'covid', 'cases', 'policy', 'transformed']
['variables', 'which', 'represent', 'policy', 'implementation']
['periods', 'including', 'weeks', 'three', 'weeks']
['month', 'months', 'months', 'scraped']
['daily', 'cumulative', 'converted', 'daily']
['growth', 'which', 'difference', 'between', 'logarithms']
['cumulative', 'numbers', 'successive', 'these']
['implementation', 'indicators', 'regressed', 'growth']
['using', 'panel', 'regression', 'analysis', 'panel', 'regression', 'widely']
['analyze', 'dimensional', 'panel', 'which', 'typically']
['cross', 'sectional', 'states', 'countries', 'longitudinal']
['month', 'dimensions', 'specifically', 'fixed', 'effects']
['panel', 'regression', 'model', 'adopted', 'study', 'could']
['model', 'unobserved', 'heterogeneity', 'through', 'state', 'specific', 'fixed']
['effects', 'addition', 'growth', 'multiplied']
['regression', 'regression', 'coefficient', 'policy']
['could', 'interpreted', 'percentage', 'point', 'changes', 'growth']
['figure']
['figure', 'scraped', 'product', 'support', 'covid', 'policy']
['analysis']
['study', 'demonstrated', 'orders']
['workplace', 'closures', 'public', 'information', 'campaigns']
['drastically', 'decrease', 'confirmed', 'growth', 'orders', 'workplace', 'closure', 'decrease', 'growth']
['through', 'changes', 'mobility', 'while', 'public', 'information', 'paign', 'impact', 'confirmed', 'growth', 'through', 'channels']
['other', 'mobility', 'addition', 'regarding', 'death', 'growth']
['orders', 'international', 'travel', 'controls']
['limited', 'mitigation', 'effect', 'relation', 'between', 'policies']
['84794', 'volume', '2021h', 'covid', 'scraper', 'source', 'toolset']
['growth', 'rates', 'learned', 'study', 'could', 'provide']
['policymakers', 'better', 'understanding', 'effectiveness']
['policy', 'support', 'decision', 'making']
['conclusion']
['covid', 'outbreak', 'impacted', 'billions', 'people']
['world', 'governments', 'organizations', 'research', 'insti', 'tutions', 'conducting', 'rapid', 'research', 'covid', 'related']
['problems', 'bring', 'people', 'every', 'country']
['normalcy', 'detailed', 'spatiotemporal', 'covid', 'records']
['proved', 'important', 'evidence', 'support', 'covid']
['related', 'research', 'however', 'collect', 'aggregate', 'store']
['share', 'published', 'country', 'world']
['community', 'effectively', 'challenge', 'solve', 'covid', 'scraper', 'developed', 'sourced']
['toolset', 'automatically', 'extract', 'collect', 'filter']
['refine', 'unify', 'store', 'public', 'spatiotemporal', 'covid']
['records', 'fifty', 'eight', 'countries', 'around', 'world', 'which']
['provide', 'available', 'covid', 'sources', 'minor']
['adjustments', 'toolset', 'accommodate', 'various', 'types']
['published', 'country', 'various', 'formats']
['scales', 'channels', 'publish', 'frequencies', 'importantly']
['countries', 'provide', 'access', 'historical']
['covid', 'automatically', 'build', 'historical', 'lections', 'support', 'research', 'repeatedly', 'certain', 'frequency']
['covid', 'scraper', 'processes', 'effective', 'manner']
['collecting', 'countries', 'world', 'within', 'single']
['about', 'minutes', 'after', 'processing']
['cleaning', 'fetched', 'unified', 'saved', 'database']
['sharing', 'daily', 'quality', 'checking', 'product']
['production', 'global', 'covid', 'github', 'repository']
['maintained', 'since', 'march', 'addition', 'visual', 'ization', 'component', 'developed', 'covid', 'scraper']
['publish', 'product', 'service', 'public']
['access']
['covid', 'scraper', 'utilized', 'scraping', 'technolo', 'science', 'related', 'fields']
['integrating', 'source', 'packages', 'tools']
['extracting', 'network', 'simulation', 'image', 'parsing', 'automation', 'covid', 'scraper', 'highly', 'flexible']
['automatic', 'toolset', 'process', 'tasks', 'unsupervised', 'under']
['users', 'settings', 'nature', 'source', 'users']
['easily', 'customize', 'sources', 'structure']
['output', 'product', 'execution', 'logic', 'processing', 'frequency']
['exception', 'handling', 'addition', 'users', 'modify']
['source', 'extend', 'collecting', 'datasets', 'other']
['purposes', 'support', 'wider', 'studies', 'tasks', 'gency', 'response', 'natural', 'disaster', 'detection', 'saving']
['lives']
['currently', 'limitation', 'quality', 'control']
['validation', 'cannot', 'fully', 'automated', 'because', 'accuracy']
['parsing', 'extracting', 'cannot', 'always', 'guaranteed']
['using', 'current', 'packages', 'hence', 'users', 'intervene']
['quality', 'control', 'process', 'image']
['product', 'quality']
['rapid', 'development', 'parsing', 'images']
['updating', 'component', 'minimize', 'human', 'intervention']
['automation', 'process']

# LSA Model
number_of_topics=1
words=word_count
model=create_gensim_lsa_model(clean_text,number_of_topics,words)
words_from_law =dict(model.show_topic(0, topn=words))##dict and encoding matrix values

dict(model.show_topic(0, topn=5))

{'covid': 0.8353615686846244,
 'imag': 0.35520141247889436,
 'detect': 0.142179572403319,
 'model': 0.12671521164640343,
 'dataset': 0.10935919846834341}

from wordcloud import WordCloud
text = dict(model.show_topic(0, topn=20))
l=list(text.keys())
wordcloud = WordCloud(width=150, height=200,max_font_size=25, max_words=20, background_color="white").generate(" ".join(l))
plt.imshow(wordcloud, interpolation='bilinear')
plt.axis("off")
plt.savefig('graph18.png')

# LSA Model
number_of_topics = 20 #
words = word_count
model = create_gensim_lsa_model(clean_text,number_of_topics,words)

a=pd.DataFrame()

for i in range(number_of_topics):
    words_science =dict(model.show_topic(i, topn=words))
    b=pd.DataFrame(words_science,index=[i])
    a=a.append(b)

a=a.transpose()

top_words = dict(model.show_topic(0,topn=5))

df = pd.DataFrame(columns=list(top_words.keys()), 
                  index = list(top_words.keys()))

l = list(top_words.keys())
print('cosine-similarity')
for i in l:
    for j in l:
            matrix=np.array([a.loc[i],a.loc[j]])
            n = s.metrics.pairwise.cosine_similarity(matrix, matrix, dense_output=True)
            df.loc[[i],[j]] = n[0,1]
print(df)

dfi.export(df, 'df_styled21.png')

cosine-similarity
              covid         imag      detect        model      dataset
covid             1  -0.00267804   0.0046269    -0.001142  -0.00296758
imag    -0.00267804            1 -0.00922806 -0.000851408  -0.00583234
detect    0.0046269  -0.00922806           1   0.00541258   -0.0051734
model     -0.001142 -0.000851408  0.00541258            1 -0.000505639
dataset -0.00296758  -0.00583234  -0.0051734 -0.000505639            1

covid-non-science.txt

document_list,titles,word_count=load_data("","covid-non-science.txt")

Number of words in text file : 8713
Total Number of Documents: 387

clean_text=preprocess_data(document_list)

['covid', 'recovery', 'covid', 'reality']
['reuters']
['published', 'updated']
['jones']
['london', 'reuters', 'world', 'shares', 'inched', 'towards', 'month', 'friday', 'industrial', 'bellwether', 'metal', 'copper', 'longest', 'weekly', 'winning', 'streak', 'nearly', 'three', 'years', 'recovering', 'global', 'nagging', 'coronavirus', 'nerves']
['market', 'rally', 'fuelled', 'record', 'numbers', 'largely', 'blown', 'itself', 'spike', 'covid', 'cases', 'though', 'fastest', 'expansion', 'china', 'services', 'sector', 'decade', 'stimulus', 'ensured', 'optimism', 'remained']
['chinese', 'shares', 'charged', 'their', 'highest', 'level', 'years', 'helping', 'asian', 'indexes', 'month', 'peaks', 'sight', 'european', 'markets', 'stalling', 'early', 'traders', 'surprise']
['currency', 'commodity', 'markets', 'subdued', 'after', 'otherwise', 'strong', 'confidence', 'sensitive', 'stalwarts', 'copper', 'sterling', 'australian', 'dollar', 'which', 'struggled', 'friday']
['think', 'infection', 'rates', 'fears', 'localised', 'lockdowns', 'doused', 'enthusiasm', 'societe', 'generale', 'strategist', 'jukes']
['three', 'elements', 'vaccine', 'hopes', 'decent', 'places', 'return', 'infection', 'rates', 'which', 'nervous']
['against', 'basket', 'currencies', 'dollar', 'slightly', 'early', 'london', 'trading', 'still', 'firmly', 'track', 'biggest', 'weekly', 'since', 'first']
['though', 'gained', 'against', 'swiss', 'franc', 'versus', 'sometimes', 'commodity', 'driven', 'norwegian', 'crown']
['futures', 'volumes', 'lower', 'usual', 'markets', 'holiday', 'friday', 'independence']
['nonfarm', 'payrolls', 'surged', 'million', 'above', 'average', 'forecast', 'million', 'thanks', 'rises', 'hospitality', 'sectors']
['economists', 'noted', 'there', 'caveats', 'upbeat', 'headline', 'figures']
['number', 'permanent', 'losers', 'continued', 'increasing', 'million', 'while', 'unemployment', 'remains', 'chunky', 'percentage', 'points', 'above', 'february', 'level', 'deutsche', 'analysis', 'unemployment', 'behind', 'developed', 'market', 'peers', 'barring', 'canada']
['recovery', 'faces', 'headwinds', 'surge', 'coronavirus', 'infections', 'prompts', 'states', 'delay', 'cases', 'reverse', 'plans', 'stores', 'reopen', 'activities', 'resume']
['three', 'dozen', 'states', 'increases', 'covid', 'cases', 'cases', 'florida', 'spiking', 'above']
['nevertheless', 'markets', 'largely', 'overlooking', 'spikes', 'taking', 'overall', 'situation', 'still', 'improving', 'overall']
['german', 'government', 'yields', 'basis', 'points', 'their', 'biggest', 'weekly', 'month', 'though', 'nudged', 'friday', 'riskier', 'italian', 'yields', 'though', 'which', 'their', 'lowest', 'since', 'march']
['prices', 'eased', 'after', 'otherwise', 'solid', 'brent', 'crude', 'barrel', 'while', 'crude', 'dropped', 'barrel', 'around', 'months']
['copper', 'prices', 'poised', 'seventh', 'consecutive', 'weekly', 'their', 'longest', 'winning', 'streak', 'nearly', 'three', 'years', 'despite', 'slight', 'easing', 'after', 'supplier', 'chile', 'assured', 'traders', 'about', 'supply']
['three', 'month', 'copper', 'hovering', 'tonne', 'ploughed', 'march']
['issue', 'hangs', 'markets', 'surge', 'secondary', 'infections', 'trigger', 'second', 'national', 'rather', 'regional', 'shutdowns', 'malcolm', 'freeman', 'director', 'kingdom', 'futures', 'wrote']
['reporting', 'jones']
['newspaper']
['covid', 'vaccine', 'frontrunners']
['reuters']
['published', 'october', 'updated', 'october']
['reuters', 'pfizer', 'could', 'november', 'authorization', 'covid', 'vaccine', 'developing', 'opening', 'possibility', 'vaccine', 'being', 'available', 'united', 'states', 'moderna', 'astrazeneca', 'close', 'behind', 'largest', 'drugmaker', 'likely', 'early', 'their', 'vaccine', 'candidates', 'before', 'potential', 'vaccines', 'being', 'developed', 'tested', 'globally', 'covid', 'pandemic', 'human', 'trials', 'according', 'world', 'health', 'organization', 'following', 'tracks', 'candidates', 'final', 'stages', 'testing', 'separate', 'factbox', 'coronavirus', 'vaccines', 'under', 'development', 'click', 'company', 'stage', 'development', 'expected', 'doses', 'pfizer', 'stage', 'trials', 'underway', 'option', 'biontech', 'pfizer', 'earlier', 'october', 'could', 'emergency', 'authorization', 'november', 'indicating', 'vaccine', 'could', 'potentially', 'available', 'additional', 'canada', 'specified', 'japan', 'moderna', 'completed', 'enrollment', 'option', 'subjects', 'stage', 'trial', 'additional', 'interim', 'results', 'trial', 'expected', 'november', 'japan', 'distributed', 'takeda', 'canada', 'specified', 'johnson', 'johnson', 'large', 'vaccine', 'trial', 'resume', 'after', 'paused', 'under', 'subsequent', 'agreement', 'illness', 'study', 'volunteer', 'results', 'trial', 'expected', 'option', 'early', 'additional', 'canada', 'japan', 'applicable', 'astrazeneca', 'stage', 'trials', 'underway', 'supply', 'deals', 'countries', 'oxford', 'university', 'trial', 'vaccine', 'candidate', 'doses', 'pause', 'since', 'after', 'patient', 'trial', 'results', 'expected', 'coming', 'weeks', 'commitment', 'deliver', 'total', 'least', 'additional', 'italy', 'germany', 'netherlands', 'france', 'additional', 'canada', 'japan', 'sinovac', 'biotech', 'stage', 'trials', 'brazil', 'vaccine', 'approved', 'emergency', 'indonesia', 'turkey', 'underway', 'china', 'supply', 'prelim', 'expected', 'november', 'indonesia', 'least', 'doses', 'before', 'gamaleya', 'research', 'stage', 'trial', 'covid', 'people', 'inoculated', 'institute', 'vaccine', 'sputnik', 'underway', 'russia', 'supply', 'deals', 'since', 'prelim', 'countries', 'including', 'india', 'expected', 'november', 'brazil', 'saudi', 'arabia', 'doses', 'cansino', 'biologics', 'vaccine', 'candidate', 'final', 'stage', 'mexico', 'doses', 'early', 'trials', 'approved', 'chinese', 'military', 'stage', 'trial', 'underway', 'pakistan', 'sinopharm', 'group', 'stage', 'trials', 'expects', 'produce', 'underway', 'billion', 'doses', 'reporting', 'dania', 'nadeem', 'mrinalika', 'bengaluru', 'editing', 'ankur', 'banerjee', 'samuel']
['newspaper']
['giants', 'another', 'covid']
['reuters']
['published', 'november', 'updated', 'november']
['giants', 'another', 'covid']
['monday', 'night', 'notified', 'player', 'tested', 'positive', 'covid', 'giants', 'announced', 'tuesday', 'morning', 'player', 'immediately', 'isolated', 'contact', 'tracing', 'process', 'initiated', 'close', 'contacts', 'staff', 'members', 'identified', 'informed', 'remain', 'today']
['giants', 'entering', 'their', 'second', 'player', 'positive', 'covid']
['prior', 'playing', 'tampa', 'buccaneers', 'offensive', 'lineman', 'hernandez', 'tested', 'positive']
['hernandez', 'spent', 'nearly', 'weeks', 'reserve', 'covid', 'returned', 'played', 'sunday', 'victory', 'philadelphia', 'eagles']
['field', 'level', 'media']
['newspaper']
['covid', 'antivirals', 'taskforce', 'launched']
['media']
['published', 'april', 'updated', 'april']
['covid', 'treatments', 'being', 'sought', 'government', 'experts', 'speed', 'recovery', 'people', 'become', 'infected', 'virus']
['government', 'taskforce', 'supercharge', 'search', 'antiviral', 'medications', 'covid']
['prime', 'minister', 'boris', 'johnson', 'group', 'medicines', 'covid', 'tracks']
['hoped', 'antivirals', 'could', 'reduce', 'infections', 'limit', 'impact', 'variants']
['protect', 'people', 'cannot', 'vaccines', 'those', 'fully', 'protected', 'after', 'having']
['officials', 'bring', 'treatments', 'online']
['could', 'people', 'covid', 'those', 'close', 'contact', 'could', 'offered', 'antiviral', 'medication', 'offered', 'tablet', 'infection', 'spreading', 'speed', 'recovery']
['antivirals', 'taskforce', 'which', 'appoint', 'chair', 'search', 'promising', 'potential', 'antiviral', 'medicines', 'which', 'taken']
['taskforce', 'support', 'development', 'drugs', 'through', 'clinical', 'trials', 'manufacturing', 'opportunities']
['antiviral', 'drugs', 'medication', 'specifically', 'treating', 'viral', 'infections', 'killing', 'preventing', 'growth', 'viruses']
['success', 'vaccination', 'programme', 'demonstrated', 'achieve', 'bring', 'together', 'brightest', 'minds', 'johnson']
['antivirals', 'taskforce', 'develop', 'innovative', 'treatments', 'covid', 'tracks']
['these', 'could', 'provide', 'another', 'vital', 'defence', 'against', 'future', 'increase', 'infections', 'lives']
['health', 'secretary', 'hancock', 'medicines', 'vital', 'weapon', 'protect', 'loved', 'terrible', 'virus']
['modelled', 'success', 'vaccines', 'therapeutics', 'taskforces', 'which', 'played', 'crucial', 'response', 'pandemic', 'bringing', 'together', 'supercharge', 'search', 'antiviral', 'treatments', 'autumn']
['government', 'chief', 'scientific', 'adviser', 'patrick', 'vallance', 'speed', 'which', 'vaccines', 'therapeutics', 'dexamethasone', 'identified', 'deployed', 'against', 'covid', 'critical', 'pandemic', 'response']
['antivirals', 'tablet', 'another', 'response']
['could', 'protect', 'those', 'protected', 'ineligible', 'vaccines']
['could', 'another', 'layer', 'defence', 'variants', 'concern']
['nikita', 'kanani', 'medical', 'director', 'primary', 'england', 'research', 'reality', 'record', 'speed', 'during', 'pandemic', 'taskforce', 'identify', 'convenient', 'treatments', 'patients', 'covid']
['commenting', 'announcement', 'penny', 'visiting', 'professor', 'pharmaceutical', 'medicine', 'kings', 'college', 'london', 'antiviral', 'treatment', 'influenza', 'shown', 'reduce', 'hospitalisation', 'prevent', 'death', 'epidemic', 'pandemic', 'waves', 'similar', 'preferably', 'simple', 'antiviral', 'suitable', 'community', 'range', 'interventions', 'critical', 'enable', 'remain', 'covid', 'pandemic', 'event', 'emergence', 'viral', 'variants', 'insensitive', 'vaccines']
['there', 'number', 'early', 'phase', 'trials', 'looking', 'antiviral', 'medications']
['newspaper']
['african', 'covid', 'deaths']
[]
['published', 'february', 'updated', 'february']
['africa', 'thursday', 'recorded', 'deaths', 'covid', 'milestone', 'likely', 'understate', 'continent', 'billion', 'people', 'battles', 'second', 'infections']
['countries', 'region', 'death', 'reported', 'cases', 'according', 'tally']
['continent', 'relatively', 'spared', 'pandemic', 'except', 'oceania', 'reach', 'threshold', 'deaths', 'which', 'europe', 'crossed', 'april']
['south', 'africa', 'worst', 'african', 'country', 'rolled', 'testing', 'campaign', 'start', 'pandemic']
['country', 'recorded', 'nearly', 'million', 'cases', 'deaths']
['those', 'figures', 'based', 'daily', 'reports', 'communicated', 'health', 'authorities', 'reflect', 'fraction', 'actual', 'health', 'specialists']
['cases', 'clearly', 'under', 'reported', 'because', 'access', 'healthcare', 'facilities', 'under', 'reporting', 'milder', 'cases', 'south', 'african', 'virologist', 'barry', 'schoub', 'member', 'scientific', 'council', 'south', 'african', 'ministry', 'health']
['understaffed', 'health', 'facilities', 'means', 'meant', 'african', 'countries', 'unable', 'testing']
['countries', 'mainly', 'tests', 'capitals', 'further', 'moves', 'urban', 'centres', 'there', 'tests', 'explained', 'french', 'epidemiologist', 'emmanuel', 'baron', 'doctors', 'without', 'borders']
['disease', 'unnoticed', 'asymptomatic', 'patients', 'symptoms', 'confused', 'others', 'added']
['covid', 'found', 'pawpaw']
['zimbabwe', 'country', 'devastated', 'economy', 'mismanaged', 'health', 'system', 'hospitals', 'filled', 'covid', 'patients', 'exhausted', 'doctors', 'overwhelmed', 'nurses', 'official', 'number', 'cases', 'remains']
['tanzania', 'stopped', 'testing', 'after', 'claiming', 'found', 'positive', 'covid', 'pawpaw', 'quail', 'tanzanian', 'government', 'released', 'official', 'figures', 'april']
['someone', 'continent', 'would', 'deaths', 'infection', 'probably', 'would', 'believed', 'nkengasong', 'africa', 'director', 'centers', 'disease', 'control', 'preventions', 'reporters', 'thursday']
['africa', 'however', 'significantly', 'lower', 'europe', 'world', 'affected', 'region', 'deaths', 'recorded', 'other', 'regions', 'badly', 'latin', 'america', 'deaths', 'united', 'states', 'canada', 'deaths']
['after', 'sharp', 'increase', 'january', 'africa', 'figures', 'fallen', 'sharply', 'weeks', 'seven', 'continent', 'recorded', 'deaths', 'percent', 'previous']
['height', 'pandemic', 'january', 'continent', 'deaths']
['disaster']
['while', 'coronavirus', 'figures', 'clearly', 'underestimated', 'health', 'disaster', 'africa', 'baron']
['several', 'studies', 'antibodies', 'which', 'possible', 'detect', 'whether', 'person', 'recovered', 'previously', 'exposed', 'virus', 'underway', 'african', 'countries', 'should', 'provide', 'better', 'impact', 'pandemic', 'region']
['south', 'africa', 'where', 'almost', 'latest', 'cases', 'attributed', 'variant', 'virus', 'known', 'contagious', 'which', 'spread', 'widely', 'represents', 'nearly', 'deaths', 'reported', 'cases', 'continent']
['other', 'african', 'countries', 'affected', 'egypt', 'deaths', 'cases', 'morocco', 'deaths', 'cases']
['south', 'africa', 'country', 'covid', 'fatalities', 'continent', 'counting', 'deaths', 'inhabitants', 'ahead', 'tunisia', 'deaths', 'eswatini']
['lagging', 'behind', 'vaccination', 'continent', 'leading', 'industrial', 'powerhouse', 'administered', 'first', 'vaccines', 'wednesday']
['globally', 'covid', 'caused', 'million', 'infections', 'million', 'deaths', 'since', 'start', 'epidemic', 'wuhan', 'china', 'december']
[]
['newspaper']
['covid', 'hotspots', 'industry']
['australian', 'associated', 'press']
['published', 'august', 'updated', 'august']
['fitness', 'industry', 'perception', 'covid', 'hotspots', 'saying', 'there', 'transmission', 'virus', 'linked']
['fitness', 'australia', 'chief', 'executive', 'barrie', 'elvish', 'fitness', 'australia', 'gathered', 'random', 'sample', 'operators', 'proves']
['since', 'reopened', 'there', 'million', 'visits', 'recorded', 'community', 'transmission']
['cannot', 'restaurants', 'where', 'cluster', 'cases', 'started', 'spread', 'however', 'still', 'being', 'categorised', 'these', 'other', 'entertainment', 'venues', 'negative', 'light', 'statement', 'thursday']
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['published', 'september', 'updated', 'september']
['easing', 'covid', 'restrictions', 'around', 'school', 'community', 'lower', 'community', 'acquired', 'covid', 'numbers']
['weddings']
['people', 'official', 'wedding', 'party', 'dance', 'floor', 'where', 'previously', 'bride', 'groom', 'permitted']
['schools']
['interschool', 'activities', 'resume', 'saturday', 'covid', 'safety']
['school', 'sport', 'return', 'normal', 'parents', 'school', 'sites']
['playing', 'instruments', 'singing', 'chanting', 'permitted', 'strict', 'restrictions']
['formals', 'graduations', 'permitted']
['school', 'formals', 'permitted', 'after']
['kindergarten', 'orientation']
['transition']
['excursions', 'camps', 'resume', 'strict', 'guidelines']
['school', 'choirs', 'musical', 'ensembles', 'resume', 'players', 'metre', 'distance', 'another', 'three', 'metres', 'players', 'reeded', 'woodwind', 'instruments']
['community', 'languages', 'schools', 'program', 'resume', 'learning']
['sport']
['parent', 'attend', 'community', 'sporting', 'activities', 'physical', 'distancing', 'least', 'metres', 'maintained']
['accommodation', 'facilities', 'overnight', 'event', 'organisers', 'implement', 'covid', 'safety']
['carpooling', 'should', 'continue', 'avoided']
['newspaper']
['zealand', 'launches', 'covid', 'diary']
['australian', 'associated', 'press']
['published', 'updated']
['belatedly', 'cases', 'covid', 'zealand', 'government', 'launched', 'covid', 'kiwis', 'track', 'their', 'movements']
['prime', 'minister', 'jacinda', 'ardern', 'launched', 'wednesday', 'labelling', 'digital', 'diary']
['differs', 'australian', 'version', 'linking', 'other', 'users']
['instead', 'allows', 'kiwis', 'check', 'different', 'venues', 'cafes', 'restaurants', 'avoid', 'onerous', 'writing', 'contact', 'details', 'every', 'place', 'visited']
['helps', 'users', 'about', 'their', 'movements', 'ardern']
['people', 'keeps', 'themselves', 'rather', 'adding', 'broader', 'repository', 'might', 'business']
['stage', 'government', 'authorities', 'though', 'functionality', 'added', 'update', 'month']
['different', 'functionality', 'means', 'there', 'threshold', 'required', 'useful', 'still', 'plenty', 'kiwis', 'taken']
['before', 'officially', 'launched', 'kiwis', 'almost', 'population', 'downloaded']
['wednesday', 'director', 'general', 'health', 'ashley', 'bloomfield', 'announced', 'there', 'cases', 'covid', 'zealand', 'fourth']
['there', 'cases', 'overall', 'fortnight']
['decreasing', 'numbers', 'nightclubs', 'first', 'since', 'march', 'thursday', 'provided', 'customers', 'seated', 'groups', 'under', 'receive', 'table', 'service']
['ardern', 'further', 'review', 'gathering', 'numbers', 'currently', 'except', 'funerals', 'which', 'monday', 'cabinet', 'meeting']
['regularly', 'adjust', 'settings', 'allow', 'activity', 'ardern']
['showing', 'virus', 'squashed', 'months', 'zealander', 'being', 'treated', 'hospital', 'covid', 'require', 'intensive']
['newspaper']
['records', 'covid', 'cases', 'deaths']
['reuters']
['published', 'updated']
['london', 'reuters', 'britain', 'reported', 'daily', 'covid', 'cases', 'government', 'figures', 'showed', 'thursday', 'slightly', 'reported', 'before', 'which', 'highest', 'daily', 'total', 'since', 'february']
['britain', 'reported', 'seven', 'further', 'deaths', 'within', 'positive', 'covid', 'wednesday', 'taking', 'total', 'death', 'measure']
['british', 'adult', 'population', 'received', 'doses', 'covid', 'vaccine', 'received', 'least', 'reporting', 'david', 'milliken', 'editing', 'holton']
['newspaper']
['drugs', 'wrongly', 'touted', 'covid', 'treatments']
['australian', 'associated', 'press']
['published', 'august', 'updated', 'august']
['medicines', 'falsely', 'touted', 'covid', 'treatments']
['hydroxychloroquine', 'treat', 'malaria', 'rheumatoid', 'arthritis', 'lupus', 'there', 'reliable', 'evidence', 'prevent', 'treat', 'covid', 'studies', 'found', 'things', 'worse']
['remdesivir', 'antiviral', 'medicine', 'people', 'hospital', 'severe', 'covid', 'recover', 'faster', 'people', 'milder', 'covid']
['dexamethasone', 'reduces', 'inflammation', 'treat', 'asthma', 'arthritis', 'reduces', 'dying', 'people', 'hospital', 'serious', 'covid', 'breathe', 'doesn', 'people', 'severe', 'covid', 'could', 'things', 'worse']
['ephedra', 'vitamin', 'other', 'complementary', 'medicines', 'found', 'effective', 'against', 'covid', 'outside', 'intensive']
['source', 'medicinewise']
['newspaper']
['covid', 'schools', 'study', 'breakdown']
['australian', 'associated', 'press']
['published', 'april', 'updated', 'april']
['national', 'centre', 'immunisation', 'research', 'surveillance', 'ncirs', 'study', 'covid', 'schools', 'found']
['total', 'students', 'staff', 'members', 'schools', 'march', 'april', 'diagnosed', 'covid']
['people', 'students', 'staff', 'members']
['those', 'people', 'total', 'close', 'contacts', 'within', 'school', 'period']
['close', 'contacts', 'people', 'caught', 'covid']
['those', 'people', 'students', 'disease', 'others']
['students', 'passed', 'coronavirus', 'school', 'staff', 'members']
['spread', 'covid', 'within', 'schools', 'limited', 'virus', 'transmission', 'children', 'schools', 'influenza']
['newspaper']
['sydney', 'repeat', 'covid', 'breaches']
['australian', 'associated', 'press']
['published', 'october', 'updated', 'october']
['sydney', 'portugal', 'community', 'being', 'forced', 'seven', 'after', 'failing', 'comply', 'covid', 'regulations', 'after', 'three', 'warnings']
['liquor', 'gaming', 'director', 'compliance', 'dimitri', 'argeres', 'portugal', 'marrickville', 'fourth', 'business', 'closed', 'covid', 'safety', 'breaches']
['close', 'wednesday']
['inspectors', 'visited', 'three', 'times', 'observed', 'breaches', 'relating', 'their', 'covid', 'safety', 'overbooking', 'groups', 'gaming', 'machine', 'spacing', 'inadequate', 'check', 'processes', 'argeres', 'tuesday']
['since', 'closure', 'order', 'issued', 'however', 'things', 'fined', 'longer', 'breaches', 'example', 'bookings', 'people', 'rather', 'while', 'guests', 'spaced', 'least', 'metres', 'apart', 'gaming', 'machines']
['changed', 'having', 'robust', 'digital', 'check', 'processes', 'allow', 'effective', 'contact', 'tracing', 'event', 'positive', 'visited', 'venue', 'argeres']
['service', 'covid', 'check', 'businesses', 'registered', 'covid', 'anyone', 'check', 'using', 'service', 'account']
['inspectors', 'liquor', 'gaming', 'trading', 'safework', 'conducted', 'covid', 'safety', 'visits', 'issued', 'penalties', 'worth', 'temporarily', 'closed', 'businesses']
['newspaper']
['tests', 'underway', 'covid', 'treatment']
['australian', 'associated', 'press']
['published', 'august', 'updated', 'august']
['australian', 'researchers', 'testing', 'treatment', 'coronavirus', 'provide', 'relief', 'those', 'infected', 'covid', 'limit', 'spread']
['professor', 'david', 'morris', 'international', 'adapted', 'cancer', 'treatment', 'known', 'bromac', 'could', 'prevent', 'virus', 'moving', 'lungs', 'carriers', 'spreading', 'other', 'people']
['trial', 'coronavirus', 'patients', 'being', 'established', 'melbourne', 'hospital', 'could', 'start', 'month']
['bromac', 'under', 'development', 'years', 'cancer', 'treatment', 'includes', 'components', 'together', 'dissolve', 'spike', 'covid', 'rendering', 'unable', 'infect', 'other', 'cells']
['agents', 'pineapple', 'enzyme', 'tested', 'after', 'observed', 'eating', 'pineapples', 'resistant', 'particular', 'gastro', 'conditions']
['taken', 'development', 'decade', 'asked', 'whether', 'adapted', 'treating', 'people', 'infected', 'covid', 'professor', 'david', 'morris', 'statement', 'monday']
['results', 'renders', 'covid', 'spike', 'ineffective', 'stopping', 'infecting', 'other', 'cells']
['results', 'treatment', 'confine', 'covid', 'throat', 'prevent', 'infection', 'infected', 'patients', 'passing', 'virus']
['hoped', 'infected', 'person', 'could', 'medication', 'first', 'signs', 'covid', 'virus', 'tracks']
['could', 'provide', 'effective', 'saving', 'lives', 'protecting', 'vulnerable', 'workers', 'preventing', 'hospitalisation', 'getting', 'people', 'infected', 'covid', 'returning', 'their', 'everyday', 'lives']
['researchers', 'stress', 'treatment', 'vaccine', 'covid', 'could', 'tandem', 'treatment', 'prevention', 'measure']

# LSA Model
number_of_topics=1
words=word_count
model=create_gensim_lsa_model(clean_text,number_of_topics,words)
words_from_non_science =dict(model.show_topic(0, topn=words))##dict and encoding matrix values

dict(model.show_topic(0, topn=5))

{'trial': -0.46149416344279787,
 'vaccin': -0.3811194487810655,
 'stage': -0.3279128258377103,
 'expect': -0.2328358984915442,
 'dose': -0.19987854999141674}

from wordcloud import WordCloud
text = dict(model.show_topic(0, topn=20))
l=list(text.keys())
wordcloud = WordCloud(width=150, height=200,max_font_size=25, max_words=20, background_color="white").generate(" ".join(l))
plt.imshow(wordcloud, interpolation='bilinear')
plt.axis("off")
plt.savefig('graph19.png')

# LSA Model
number_of_topics = 20 #
words = word_count
model = create_gensim_lsa_model(clean_text,number_of_topics,words)

a=pd.DataFrame()

for i in range(number_of_topics):
    words_non_science =dict(model.show_topic(i, topn=words))
    b=pd.DataFrame(words_non_science,index=[i])
    a=a.append(b)

a=a.transpose()

top_words = dict(model.show_topic(0,topn=5))

df = pd.DataFrame(columns=list(top_words.keys()), 
                  index = list(top_words.keys()))

l = list(top_words.keys())
print('cosine-similarity')
for i in l:
    for j in l:
            matrix=np.array([a.loc[i],a.loc[j]])
            n = s.metrics.pairwise.cosine_similarity(matrix, matrix, dense_output=True)
            df.loc[[i],[j]] = n[0,1]
print(df)

dfi.export(df, 'df_styled22.png')

cosine-similarity
           trial    vaccin     stage    expect      dose
trial          1  0.234131  0.968477  0.899478  0.752671
vaccin  0.234131         1  0.250697  0.297949  0.630685
stage   0.968477  0.250697         1  0.951998  0.784867
expect  0.899478  0.297949  0.951998         1   0.79207
dose    0.752671  0.630685  0.784867   0.79207         1

covid-psychology.txt

document_list,titles,word_count=load_data("","covid-psychology.txt")

Number of words in text file : 86550
Total Number of Documents: 9007

clean_text=preprocess_data(document_list)

['international', 'sociology']
[]
['author']
['article', 'reuse', 'guidelines']
['sagepub', 'journals', 'permissions']
['0268580920948807']
['journals', 'sagepub']
['psychology', 'politics']
['covid', 'misinfodemics']
['people']
['believe', 'misinfodemics']
['sonia', 'mukhtar']
['university', 'management', 'technology', 'lahore', 'pakistan']
['abstract']
['misinfodemics', 'related', 'covid', 'negatively', 'impacted', 'people', 'lives', 'adverse']
['health', 'psycho', 'sociopolitical', 'outcomes', 'scientific', 'community', 'seeks', 'communicate']
['evidence', 'based', 'information', 'regarding', 'misplaced', 'preventive', 'strategies', 'misinformed', 'helpseeking', 'behaviors', 'global', 'multifaceted', 'systems', 'secondary', 'emerged', 'effects']
['misinfodemics', 'public', 'published', 'articles', 'pubmed', 'embase', 'google', 'scholar', 'elsevier']
['about', 'covid', 'related', 'misinfodemics', 'considered', 'reviewed', 'article']
['review', 'examines', 'mechanisms', 'operational', 'structure', 'prevalence', 'predictive', 'factors', 'effects']
['responses', 'potential', 'curtailing', 'strategies', 'misinfodemics', 'covid', 'present', 'article']
['shows', 'popular', 'variants', 'covid', 'misinfodemics', 'could', 'joint', 'product']
['psychological', 'predisposition', 'which', 'either', 'reject', 'information', 'experts', 'perceive']
['crisis', 'situation', 'product', 'misinfodemics', 'mechanisms', 'partisan', 'ideological', 'motivations']
['psychological', 'foundations', 'political', 'disposition', 'misinfodemics', 'implications']
['development', 'strategies', 'designed', 'curtail', 'negative', 'consequences', 'public', 'health']
['keywords']
['conspiracy', 'theories', 'covid', 'health', 'communication', 'misinformation', 'mistrust', 'science']
['mechanisms', 'misinfodemics']
['modern', 'mainstream', 'social', 'media', 'become', 'primary', 'source', 'information', 'people', 'around', 'world', 'misinfodemics', 'surrounding']
['corresponding', 'author']
['sonia', 'mukhtar', 'university', 'management', 'technology', 'block', 'phase', 'johar', 'lahore']
['punjab', '54770', 'pakistan']
['email', 'sonia', 'mukhtar12', 'gmail']
['948807iss0010', '0268580920948807international', 'sociologymukhtar']
['research', 'article2020']
['article']
['international', 'sociology']
['covid', 'pandemic', 'challenging', 'ongoing', 'coronavirus']
['covid', 'pandemic', 'outbreak', 'highlighted', 'interconnectedness', 'modern']
['globalized', 'world', 'where', 'public', 'health', 'threats', 'extend', 'beyond', 'their', 'point', 'origin']
['unvarying', 'reliance', 'misplaced', 'confidence', 'media', 'platforms', 'during']
['lockdown', 'quarantine', 'isolation', 'social', 'distancing', 'virtual', 'communication']
['become', 'major', 'source', 'interaction', 'holman']
['covid', 'pandemic', 'outbreak', 'escalated', 'challenges']
['healthcare', 'social', 'educational', 'economic', 'political', 'environmental', 'cultural', 'socioeconomic', 'systems', 'world', 'gained', 'momentum', 'innumerable']
['misinfodemics', 'mechanisms', 'rumors', 'myths', 'superstitions', 'conspiracy', 'theories']
['claims', 'hoaxes', 'false', 'misinformation', 'polarization', 'mistrust', 'science']
['times', 'crisis', 'absence', 'checking', 'misinformation', 'misleading', 'content', 'false']
['context', 'manipulated', 'fabricated', 'material', 'imposter', 'documents', 'disinformation', 'regarding', 'etiology', 'outcomes', 'misplaced', 'prevention', 'disease']
['mukhtar', '2020a']
['covid', 'pandemic', 'outbreak', 'saturated', 'mainstream', 'media', 'which', 'disseminate', 'information', 'local', 'global', 'scale', 'similarly', 'social', 'media', 'platforms']
['become', 'accessible', 'source', 'information', 'numerous', 'incidents', 'initiated']
['these', 'rumors', 'caused', 'several', 'mishaps', 'across', 'world', 'instance']
['after', 'positive', 'diagnosis', 'covid', 'india', 'people', 'overdosed']
['cholorquine', 'after', 'about', 'effectiveness', 'against', 'covid', 'proliferated', 'nigeria', 'busari', 'adebayo', 'there', 'failure']
['distinction', 'between', 'empirically', 'based', 'scientific', 'truths', 'fabricated', 'unconfirmed']
['science', 'conspiracy', 'theories', 'among', 'general', 'public', 'reports', 'reduce', 'legitimacy', 'scientific', 'discoveries', 'regarding', 'vaccine', 'covid']
['create', 'social', 'stigma', 'resulting', 'xenophobia', 'chinese', 'sentiment', 'racism', 'marginalization', 'reduced', 'compliance', 'adherence', 'quarantine', 'adverse', 'health']
['psychosocial', 'impacts', 'aguilera', '2020a', '2020b', 'these', 'considerations', 'become', 'exacerbated', 'during', 'lockdown', 'leading', 'people', 'fringe']
['popular', 'opinion', 'spend', 'social', 'media', 'people', 'trying']
['sense', 'their', 'changed', 'lives', 'proclaimed', 'celebrities', 'identified', 'social']
['media', 'stars', 'politicians', 'mainstream', 'media', 'public', 'figures', 'propagating', 'their']
['subjective', 'interpretations', 'events', 'situation', 'covid', 'pandemic', 'misinfodemics', 'lederer']
['scientific', 'studies', 'previous', 'disease', 'outbreaks', 'demonstrated', 'misinformation', 'represents', 'secondary', 'challenge', 'public', 'health', 'efforts', 'controlling', 'epidemic', 'pandemic', 'earnshaw', 'kalichman', 'individuals', 'endorse']
['misinformation', 'about', 'disease', 'likely', 'follow', 'public', 'health', 'instructions', 'during']
['ebola', 'outbreak', 'respondents', 'credence', 'conspiracy', 'theories']
['alleged', 'would', 'likely', 'support', 'during', 'disease', 'outbreak']
['national', 'cancer', 'institute', 'study', 'montanaro', 'conducted']
['respondents', 'reported', 'trust', 'medical', 'healthcare', 'professionals', 'contrast', 'study', 'where', 'majority', 'respondents', 'reported', 'mistrust', 'information']
['about', 'covid', 'current', 'administration', 'mainstream', 'media', 'outlets']
['times']
['mukhtar']
['psychology', 'misinfodemics']
['adaptive', 'emotion', 'which', 'serves', 'mobilize', 'energy', 'towards', 'potential', 'actual']
['perceived', 'threat', 'mertens', 'however', 'excessive']
['detrimental', 'effects', 'individual', 'mental', 'health', 'problems', 'anxiety']
['phobia', 'community', 'level', 'hoarding', 'panic', 'shopping', 'xenophobia']
['insufficient', 'cause', 'individual', 'incompliance', 'nonadherence', 'towards', 'quarantine', 'isolation', 'community', 'reckless', 'implementation']
['policies', 'ignores', 'risks', 'socioeconomic', 'infrastructure', 'likewise', 'interpersonal']
['safety', 'measures', 'mitigate', 'certain', 'threats', 'transmission', 'disease', 'paradoxically', 'enhance', 'transmission', 'excessive', 'health', 'anxiety', 'psychosocial']
['issues', 'similarly', 'social', 'safety', 'measures', 'lockdowns', 'curfews', 'control', 'transmission', 'prolonged', 'stringent', 'measures', 'could', 'negative', 'consequences', 'socioeconomic', 'impact', 'mental', 'health', 'impact']
['efforts', 'misinfodemics', 'process', 'increased', 'because', 'adverse']
['effects', 'public', 'health', 'communication', 'encourage', 'adoption', 'sustainable']
['preventive', 'measures', 'manage', 'social', 'physical', 'distancing', 'psychological', 'health']
['resilience', 'socioeconomic', 'conditions', 'address', 'stigma', 'prejudice', 'discrimination']
['inequalities', 'mukhtar', '2020b', 'among', 'various', 'factors', 'psychological', 'vulnerability', 'mukhtar', '2020c', 'mukhtar', 'mahmood', 'propensity', 'follow', 'popular']
['opinion', 'excessive', 'social', 'media', 'presence', 'predisposition', 'anxiety']
['uncertainty', 'intolerance', 'unpredictability', 'coronavirus', 'brings', 'levels', 'uncertainty', 'inability', 'uncertainty', 'exponentially', 'higher', 'causing', 'anxiety']
['health', 'related', 'worry', 'situation', 'exacerbated', 'exposure', 'plethora']
['information', 'including', 'misinformation', 'disinformation', 'about', 'impending']
['threat', 'mainstream', 'media', 'social', 'media', 'alike', 'rosser', 'perceived', 'threat']
['information', 'elevates', 'repeated', 'engagement', 'trauma', 'related', 'media', 'content']
['several', 'hours', 'daily', 'culminates', 'acute', 'stress', 'emotional', 'distress', 'consequently']
['either', 'increase', 'virus', 'cause', 'insensitivity', 'towards', 'course']
['identification', 'monitoring', 'internet', 'centrifugal', 'clarification', 'filter']
['accuracy', 'content', 'become', 'challenging', 'increasing', 'number', 'people']
['social', 'media', 'platforms', 'challenging', 'problems', 'misinformation', 'disinformation', 'conspiracy', 'theories', 'social', 'media', 'emulsify', 'false']
['misleading', 'click', 'content', 'world', 'health', 'organization', 'launched']
['mythbuster', 'feature', 'website', 'countermeasure', 'spread', 'unauthentic']
['social', 'media', 'people', 'reported', 'highest', 'media', 'exposure', 'reported', 'higher']
['acute', 'stress', 'holman', 'media', 'exposure', 'accumulates', 'emerging', 'threats']
['repeated', 'exposure', 'these', 'events', 'increase', 'symptoms', 'distress', 'worry', 'fixation']
['mentality', 'misplaced', 'conviction', 'people', 'vulnerable', 'media', 'exposure', 'distress']
['alongside', 'amount', 'media', 'exposure', 'content', 'exposure', 'matters']
['exposure', 'tragic', 'events', 'graphic', 'images', 'conspiracy', 'theories', 'violence', 'could']
['instigate', 'posttraumatic', 'stress', 'future', 'which', 'personal']
['functioning', 'recent', 'years', 'mainstream', 'media', 'electronic', 'print', 'social', 'media']
['established', 'themselves', 'beyond', 'government', 'channel', 'global']
['international', 'sociology']
['population', 'developed', 'affinity', 'channels', 'particular', 'while', 'older']
['population', 'mainly', 'relies', 'traditional', 'channels', 'youth', 'social', 'media']
['tiktok', 'instagram', 'youtube', 'twitter', 'facebook', 'whatsapp', 'social', 'media']
['become', 'conduit', 'spreading', 'rumors', 'deliberate', 'misinformation', 'disinformation', 'conspiracy', 'theories', 'personally', 'motivated', 'anecdotes', 'appeal', 'followers']
['attract', 'attention', 'create', 'panic', 'liang', 'proclaimed', 'celebrities', 'media', 'stars', 'become', 'influential', 'large', 'number', 'people', 'solely']
['their', 'content', 'merchant', 'social', 'media', 'posts', 'circulating']
['platforms', 'endorsed', 'multiple', 'social', 'media', 'account', 'users', 'encourage', 'optimal']
['personal', 'functioning', 'maximum', 'productivity', 'business', 'oriented', 'activities', 'downplaying', 'intensity', 'traumatic', 'event', 'certain', 'posts']
['quarantine', 'skill', 'hustle', 'started', 'knowledge']
['never', 'lacked', 'lacked', 'discipline', 'circulating', 'various', 'social', 'media', 'accounts']
['prompting', 'people', 'utilize', 'their', 'learning', 'things', 'skills', 'exacerbate']
['worry', 'already', 'anxiety', 'prone', 'individuals', 'place', 'psychological', 'pressure', 'productive', 'rather', 'messages', 'quarantine', 'skill']
['hustle', 'started', 'knowledge', 'doing', 'should', 'disseminated', 'social', 'media', 'individuals', 'realize', 'during', 'intense', 'traumatic', 'event', 'everyone', 'equally', 'endowed', 'strength', 'coping', 'strategies']
['problem', 'solving', 'skills', 'transform', 'trauma', 'positive', 'emotion', 'which']
['source', 'shame', 'guilt']
['there', 'coercive', 'impression', 'percolating', 'among', 'individuals', 'regarding', 'lockdown']
['people', 'should', 'assume', 'holiday', 'utilize', 'their', 'productively', 'engage', 'occupational', 'academic', 'activities', 'psychological', 'pressure']
['further', 'aggravated', 'feelings', 'guilt', 'shame', 'regret', 'sadness', 'anger', 'internalized']
['emotions', 'being', 'overwhelmed', 'negative', 'unrealistic', 'expectations', 'perceived', 'sense', 'failure', 'mukhtar', '2020a', '2020b', 'psychological', 'pressure', 'compete', 'peers', 'achieving', 'maximum', 'tasks', 'producing', 'occupational', 'academic']
['outcomes', 'harnessing', 'followers', 'subscribers', 'media', 'accounts']
['downplaying', 'trauma', 'others', 'devastating', 'effects', 'mental']
['wellbeing']
['lockdown', 'resulting', 'isolation', 'quarantine', 'social', 'distancing', 'removed']
['normal', 'leisure', 'might', 'utilized', 'improved', 'personal', 'functioning']
['collective', 'traumatic', 'event', 'which', 'poses', 'serious', 'threat', 'people', 'resulted']
['lives', 'displacement', 'individuals', 'mukhtar', 'mukhtar', 'mukhtar']
['covid', 'individual', 'collective', 'traumatic', 'event', 'directly']
['indirectly', 'affected', 'every', 'individual', 'world', 'efforts', 'should', 'directed', 'towards']
['minimizing', 'negative', 'effects', 'traumatic', 'covid', 'pandemic', 'survivors']
['people', 'going', 'through', 'interpersonal', 'traumatic', 'events', 'addition', 'collective']
['trauma', 'covid', 'domestic', 'violence', 'gender', 'based', 'violence', 'abuse', 'mukhtar', '2020d']
['financial', 'burden', 'loneliness', 'emotional', 'behavioral', 'problems', 'grief', 'bereavement']
['losing', 'family', 'mental', 'health', 'issues', 'physical', 'injuries', 'fatalities']
['isolated', 'people', 'facing', 'psychological', 'issues', 'require', 'trauma', 'focused', 'psychological']
['support', 'mental', 'health', 'psychological', 'support', 'guidance', 'treatment', 'intervention']
['information', 'psychological', 'cyber', 'counseling', 'smartphone']
['mukhtar']
['instance', 'mental', 'health', 'hotlines', 'professional', 'seeking', 'behaviors', 'should']
['encouraged', 'endorsed', 'related', 'barriers', 'stigma', 'marginalization', 'discrimination', 'shaming', 'phobias', 'should', 'discouraged', 'through', 'government', 'driven', 'programs']
['evidence', 'based', 'treatment', 'models']
['emerging', 'pandemics', 'command', 'intellectual', 'incapacity', 'decision', 'making']
['degree', 'irrationality', 'bombarded', 'conflicting', 'opinions', 'conspiracy', 'theories', 'empirical', 'interpretation', 'origins', 'impacts', 'result', 'moral', 'judgments']
['based', 'religious', 'cultural', 'beliefs', 'emergence', 'garnered', 'plethora']
['moral', 'judgments', 'orbiting', 'around', 'sexual', 'morality', 'substance', 'abuse', 'arrival']
['blame', 'directed', 'towards', 'primitive', 'farming', 'practices', 'guangzhou']
['unprecedented', 'covid', 'pandemic', 'welcomed', 'magnitude', 'misinfodemics']
['multitude', 'fronts', 'ophir', 'richtel', 'psychological', 'predisposition', 'reject']
['authorized', 'information', 'through', 'denial', 'byproduct', 'founded', 'mistrust']
['tendency', 'major', 'social', 'political', 'events', 'through', 'conspiracies', 'partisan', 'motivations', 'byproduct', 'conspiracy', 'thinking', 'likely', 'explanatory', 'factors', 'understanding', 'believes', 'covid', 'misinfodemics', 'association', 'between']
['conspiracy', 'thinking', 'defense', 'mechanism', 'denial', 'could', 'potential', 'reason']
['refusal', 'corrective', 'actions', 'several', 'health', 'related', 'cases', 'carey']
['misinfodemics', 'could', 'motivated', 'various', 'factors', 'epistemic', 'desire', 'causal']
['explanation', 'subjective', 'certainty', 'existential', 'desire', 'control', 'security']
['social', 'desire', 'maintain', 'positive', 'image', 'group', 'douglas']
['stigmatization', 'labeling', 'scapegoating', 'swiftly', 'follow', 'narrative', 'which']
['invokes', 'vernacular', 'human', 'conflict', 'waging', 'against', 'killer', 'virus', 'indomitable', 'invisible', 'threat', 'enemy', 'armed', 'vaccine', 'flinging', 'victims', 'quarantine']
['camps', 'losing', 'sense', 'proportion', 'ability', 'mitigate', 'reasonable']
['knowledge', 'based', 'measures', 'challenge', 'normalize', 'perceived', 'threat', 'infection']
['mechanism', 'misinfodemics', 'engrossed', 'silos', 'public', 'information', 'which']
['inept', 'limiting', 'risks', 'instance', 'social', 'theme', 'focusing', 'socioeconomic', 'disruption', 'scientific', 'theme', 'focusing', 'medical', 'health', 'communication', 'pandemic', 'theme', 'focusing', 'state', 'global', 'response', 'populations']
['likely', 'affected', 'emerging', 'disease', 'pandemic', 'simultaneous', 'misinfodemics']
['include', 'those', 'where', 'there', 'disproportionally', 'inadequate', 'health', 'literacy', 'disadvantaged', 'socioeconomic', 'groups', 'migrants', 'ethnic', 'minorities', 'vulnerable', 'groups']
['including', 'older', 'people', 'people', 'chronic', 'health', 'conditions', 'people', 'disability']
['mukhtar', '2020e', 'rowlands']
['politics', 'coronavirus']
['conspiracy', 'theories', 'heavily', 'influenced', 'geopolitics', 'spread', 'regarding', 'origin']
['scale', 'prevention', 'treatment', 'diagnosis', 'disease', 'covid', 'being', 'viral']
['bioweapon', 'genetically', 'engineered', 'rogue', 'government', 'racist', 'genocidal']
['agenda', 'economic', 'psychological', 'chinese', 'biological', 'weapon']
['conspiracy', 'theory', 'which', 'spread', 'throughout', 'united', 'states', 'united', 'kingdom']
['india', 'ukraine', 'biological', 'weapon', 'conspiracy', 'theory', 'spread', 'throughout']
['russia', 'china', 'philippines', 'venezuela', 'muslims']
['international', 'sociology']
['espionage', 'population', 'control', 'scheme', 'medical', 'misinformation', 'vaccine', 'preexistence', 'cocaine', 'african', 'resistance', 'vegetarian', 'immunity', 'methanol']
['other', 'views', 'endorsed', 'presidents', 'governments', 'public', 'figures', 'abound', 'causing']
['misinfodemics', 'incorrect', 'information', 'about', 'virus', 'which', 'poses', 'risks']
['global', 'scale', 'mccarthy']
['meanwhile', 'covid', 'could', 'positively', 'viewed', 'through', 'partisan']
['right', 'nationalism', 'pandemonium', 'allegations', 'coronavirus']
['politics', 'misinfodemics', 'censorship', 'pathological', 'nationalism', 'multitude']
['governments', 'introduced', 'policy', 'blame', 'shifting', 'launching', 'their', 'powerrivalry', 'statements', 'revolving', 'around', 'illogical', 'reasoning', 'narrative', 'national']
['immunity', 'towards', 'covid', 'there', 'claims', 'biological', 'weapon']
['against', 'western', 'world', 'chinese', 'experiment', 'wrong', 'china', 'equivalent']
['level', 'threat', 'infamous', 'chinese', 'virus', 'italy', 'accused', 'migrants']
['africa', 'disease', 'carriers', 'shores', 'france', 'hungary', 'there']
['narration', 'correlation', 'between', 'immigrants', 'coronavirus', 'reminiscent']
['influx', 'migrants', 'inflicted', 'countries', 'called', 'border']
['crisis', 'european', 'right', 'wingers', 'declare', 'enemy', 'changed', 'migrants']
['convergence', 'crises', 'aggravates', 'mistrust', 'scientific', 'political']
['economic', 'bodies', 'around', 'world', 'these', 'narratives', 'imply', 'through', 'heavily', 'nuanced']
['differential', 'discourse', 'their', 'countries', 'immune', 'coronavirus', 'would']
['contracted', 'covid', 'could', 'manage', 'effectively', 'absence']
['immigrants', 'mccarthy']
['covid', 'provided', 'fodder', 'europe', 'nativist', 'populist', 'further']
['incite', 'clamor', 'immigrants', 'building', 'walls', 'closing', 'borders', 'immigration', 'policies', 'public', 'opinions', 'shaped', 'landscape', 'media', 'scientific', 'bodies']
['frameworks', 'governments', 'obstinate', 'prejudice', 'confrontations']
['ignite', 'globalization', 'nationalism', 'nativism', 'protectionism', 'tariffs', 'closed', 'borders']
['erection', 'walls', 'which', 'intensify', 'covid', 'pandemic', 'outbreak']
['pakistan', 'research', 'study', 'conducted', 'ipsos', 'revealed', 'people']
['country', 'believed', 'performing', 'ablution', 'protected', 'transmitting']
['coronavirus', 'others', 'believed', 'congregation', 'prayers', 'shaking', 'hands', 'cannot']
['infect', 'anyone', 'since', 'sunnah', 'samaa', 'claims', 'circulating', 'about', 'pakistanis']
['resistance', 'coronavirus', 'quite', 'prevalent', 'backed', 'pakistan', 'relatively', 'mortality', 'these', 'rumors', 'argued', 'pakistan', 'culture', 'religion', 'geographical', 'location', 'climate', 'pakistanis', 'vulnerable', 'virus', 'india']
['political', 'activists', 'claimed', 'drinking', 'urine', 'applying']
['coronavirus', 'parliamentarian', 'claimed', 'saying', 'namaste', 'instead']
['greetings', 'prevents', 'contraction', 'coronavirus', 'influential', 'celebrity', 'claimed']
['vibrations', 'generated', 'clapping', 'blowing', 'conch', 'shells', 'virus', 'selfproclaimed', 'tiktok', 'media', 'claim', 'about', 'eating', 'poisonous', 'fruit', 'preventive']
['measure', 'hospitalized', 'people', 'coronavirus', 'coronavirus']
['mattress', 'quite', 'prevalent', 'example', 'popular', 'various', 'countries']
['remedies', 'prevent', 'people', 'contracting', 'coronavirus']
['these', 'rumored', 'remedies', 'gained', 'traction', 'social', 'media', 'severe', 'adverse']
['effects', 'involves', 'mixing', 'sodium', 'chlorite', 'solution', 'citric', 'producing', 'chlorine']
['mukhtar']
['dioxide', 'powerful', 'bleaching', 'agent', 'claiming', 'antimicrobial', 'antiviral', 'antibacterial']
['benefits', 'similar', 'phenomena', 'observed', 'world', 'which', 'prolonged', 'health', 'psychosocial', 'economic', 'consequences', 'covid', 'among']
['general', 'public']
['becomes', 'difficult', 'limit', 'negative', 'impact', 'misinfodemics', 'especially']
['partisanship', 'mobilized', 'effort', 'there', 'could', 'three', 'strategies', 'overcome']
['these', 'negative', 'effects', 'prevention', 'strategies', 'limit', 'spread', 'exposure', 'misinfodemics', 'corrective', 'strategies', 'founded', 'scientific', 'empirical']
['knowledge', 'challenge', 'these', 'predispositions', 'their', 'effects', 'subsequent', 'belief', 'system']
['reduce', 'uncertainty', 'increase', 'perceived', 'control', 'promote', 'image', 'collaborative', 'strategies', 'corrective', 'strategies', 'efficacious', 'other', 'political', 'social', 'agents']
['activated', 'mobilized', 'override', 'partisan', 'ideological', 'motivations', 'misinfodemics', 'tendencies', 'politics', 'media', 'promote', 'misinformation', 'likeminded', 'individuals', 'exposed', 'rhetoric', 'likely', 'follow', 'elite', 'motivated', 'reasoning']
['engage', 'these', 'ideas', 'partisan', 'elites', 'potential', 'inflame']
['foster', 'misinfodemics', 'shape', 'landscape', 'information', 'general', 'public']
['swire', 'instance', 'outset', 'covid', 'american', 'political', 'administration', 'referred', 'covid', 'rieder', 'likened', 'pandemic']
['common', 'brooks', 'coronavirus', 'bioweapon', 'stevenson', 'rhetoric', 'likely', 'encourage', 'adoption', 'related', 'beliefs', 'likeminded', 'supporters']
['threat', 'seriously', 'media', 'outlets', 'including', 'personalities', 'media', 'figures']
['aspersion', 'threat', 'covid', 'questioning', 'hospitals', 'truly', 'filled']
['coronavirus', 'infected', 'patients', 'peters', 'after', 'human', 'became', 'increasingly', 'apparent', 'unassailable', 'change', 'reporting', 'behavior', 'media']
['political', 'leaders', 'previously', 'explicitly', 'unequivocally', 'trafficked', 'misinfodemics', 'hinted', 'possibility', 'misinformation', 'having', 'actually', 'served', 'correct', 'prevent', 'negative', 'consequences', 'among', 'general', 'public']
['animosity', 'wrapped', 'hatred', 'inside', 'hostility']
['media', 'channels', 'initially', 'racially', 'labeled', 'biased', 'headlines', 'covid']
['chinese', 'virus', 'pandemonium', 'china', 'china']
['chinese', 'coronavirus', 'which', 'caused', 'xenophobia', 'misperceptions']
['misled', 'general', 'public', 'witnessed', 'surge', 'chinese', 'sentiment', 'racist', 'driven']
['cases', 'against', 'individuals', 'chinese', 'origin', 'outside', 'china', 'chinese', 'asian', 'xenophobia', 'reported', 'countries', 'including', 'australia']
['european', 'countries', 'chinese', 'customers', 'refused', 'entrance', 'restaurants']
['japan', 'south', 'korea', 'vietnam', 'indonesia', 'amnesty', 'international']
['office', 'united', 'nations', 'commissioner', 'human', 'rights', 'ohchr']
['issued', 'statement', 'twitter', 'understandable', 'alarmed', 'coronavirus']
['amount', 'excuse', 'prejudice', 'discrimination', 'against', 'people', 'asian', 'descent']
['fightracism', 'hatred', 'support', 'other', 'public', 'health']
['emergency', 'standup4humanrights']
['similar', 'response', 'twitter', 'began', 'jenesuispasunvirus', 'virus', 'after']
['french', 'newspaper', 'front', 'headline', 'yellow', 'alert', 'ontario', 'human', 'rights']
['international', 'sociology']
['commission', 'stated', 'discrimination', 'prohibited', 'under', 'human', 'rights']
['aguilera', 'ontario', 'human', 'rights', 'commission']
['government', 'dilemma']
['writing', 'government', 'pakistan', 'under', 'leadership', 'prime', 'minister']
['imran', 'witnessed', 'sudden', 'setback', 'number', 'cases', 'steadily']
['increasing', 'their', 'challenge', 'curtail', 'disease', 'pakistan', 'however', 'there']
['bigger', 'dilemma', 'government', 'pakistan', 'facing', 'partial']
['lockdown', 'lockdown', 'either', 'message', 'common', 'intention', 'minimize', 'urgency', 'severity', 'pandemic', 'downplay', 'social', 'isolation', 'measures', 'disregard', 'potential', 'crisis', 'health', 'sector', 'while', 'exaggerating', 'impact']
['economy', 'recession', 'looms', 'horizon', 'overlook', 'mitigating', 'measures', 'necessary', 'transmission', 'medical', 'mistrust', 'among', 'public', 'alwan']
['religion', 'politics', 'business', 'fundamentally', 'governing']
['aspects', 'pakistan', 'opposed', 'lockdown', 'putting', 'pressure', 'government', 'consequently', 'resulting', 'lifting', 'lockdown', 'pakistan', 'pandemic', 'pandemic', 'hardline', 'clerics', 'power', 'override', 'government', 'social', 'distancing']
['instructions', 'place', 'april', 'dozens', 'known', 'clerics', 'signed', 'letter']
['warning', 'government', 'should', 'exempt', 'mosques', 'shutdown', 'during']
['month', 'ramadan', 'otherwise', 'invite', 'wrath', 'ulterior', 'narrative', 'insinuating']
['political', 'chaos', 'clerics', 'unleashed', 'exercising', 'their', 'religious', 'authority']
['gather', 'loyalists', 'siege', 'state', 'subservient', 'state', 'already', 'signed']
['agreement', 'deferentially', 'promising', 'abide', 'begging', 'question']
['charge', 'government', 'during', 'pandemic', 'crisis', 'government', 'mosques']
['physical', 'mental', 'health', 'social', 'interpersonal', 'factors', 'including', 'intimate', 'partner']
['violence', 'marital', 'child', 'abuse', 'domestic', 'violence', 'racism', 'xenophobia', 'dissociation']
['prejudice', 'stigmatization', 'marginalization', 'least', 'pakistani', 'clerics']
['mosques', 'concerns', 'during', 'public', 'crisis', 'clerics', 'protect', 'their', 'central', 'interests', 'money', 'power', 'millions', 'dollars', 'charitable', 'donations', 'during', 'ramadan', 'benefit', 'pakistan', 'mosques', 'which', 'under', 'state', 'authority', 'clerics', 'often']
['partake', 'political', 'power', 'challenge', 'government', 'despite', 'evidence', 'prevalent', 'rhetoric', 'undermining', 'covid', 'related', 'risks', 'endorsed', 'austerely']
['followed', 'public', 'highest', 'level', 'authority', 'pakistan', 'clerics']
['religious', 'misinfodemics', 'branch', 'clerics', 'superciliously', 'propagated', 'doctrine', 'narrated', 'through', 'pandemic', 'religious', 'explanation', 'could']
['allowed', 'disease', 'emerge', 'through', 'rigorous', 'devotion', 'congregational']
['prayer', 'followers', 'faith', 'conquer', 'devil', 'machinations', 'coronavirus', 'anyone', 'tries', 'these', 'efforts', 'these', 'zionist', 'agents', 'pawns']
['destroying', 'faith', 'dogmatic', 'doctrine', 'seeps', 'through', 'present']
['omniscient', 'online', 'media', 'infiltrate', 'minds', 'sheeple', 'votary', 'conformists', 'usually', 'heads', 'household', 'enforce', 'these', 'maladaptive', 'cognitive', 'twisted', 'patterns']
['within', 'their', 'families', 'these', 'instructions', 'dictated', 'higher', 'authorities', 'their']
['adherence', 'infringing', 'individual', 'rights', 'freedom', 'planting', 'unquestionable']
['canon', 'propagating', 'science', 'medical', 'mistrust', 'among', 'public', 'putting', 'people']
['mukhtar']
['halting', 'emergency', 'control', 'preventive', 'measures', 'necessary']
['pandemic', 'creating', 'public', 'panic', 'social', 'unrest', 'distrust', 'systems']
['strong', 'these', 'eschewed', 'beliefs', 'result', 'adverse', 'behavioral', 'consequences', 'instance', 'failing', 'administer', 'polio', 'vaccination', 'children', 'attributing', 'islamic', 'contributing', 'resurgence', 'eradicated', 'disease']
['pakistan', 'misinfodemics', 'especially', 'those', 'which', 'revolve', 'around', 'science', 'medicine']
['health', 'related', 'topics', 'widespread', 'prompting', 'people', 'eschew', 'appropriate', 'healthrelated', 'behaviors', 'jolley', 'douglas', 'oliver']
['potential', 'strategies', 'curtailment']
['research', 'predicted', 'there', 'psychosocial', 'stress', 'adverse', 'health', 'outcomes']
['people', 'isolation', 'social', 'distancing', 'quarantine', 'crisis', 'situation']
['require', 'remediation', 'credible', 'sources', 'information', 'these', 'include']
['example', 'centers', 'disease', 'control', 'prevention', 'national', 'institutes']
['health', 'especially', 'which', 'partnered', 'several', 'social', 'media']
['platforms', 'technological', 'companies', 'google', 'linkedin', 'microsoft', 'reddit', 'twitter']
['facebook', 'youtube', 'promote', 'health', 'updates', 'misinformation', 'disinformation', 'hossain', 'seeking', 'safeguard', 'ensure', 'effective', 'communication', 'covid', 'between', 'healthcare', 'systems', 'general', 'public', 'despite']
['these', 'efforts', 'infodemics', 'rampant', 'multiple', 'misinformation', 'disinformation']
['sources', 'circulating', 'social', 'media', 'accounts', 'address', 'these', 'discrepancies', 'certain']
['strategies', 'implemented', 'empirically', 'evidence', 'based', 'scientific', 'research', 'findings']
['integration', 'communication', 'information', 'technology', 'frontline', 'healthcare', 'providers', 'communicate', 'patients', 'caregivers', 'populations']
['results', 'positive', 'health', 'outcomes', 'subsequent', 'optimization', 'resources']
['building', 'strategic', 'partnerships', 'local', 'global', 'levels', 'coordinate', 'connecting', 'offline']
['online', 'resources', 'communication', 'uniform', 'information', 'across', 'platforms', 'media', 'community', 'organizations', 'support', 'groups', 'community']
['society', 'contain', 'infodemics', 'information', 'disinformation', 'disseminate']
['scientifically', 'evidence', 'based', 'information', 'through', 'mining', 'algorithms', 'detect']
['remove', 'those', 'propagate', 'misinformation']
['accountable', 'individuals', 'online', 'portals', 'should', 'identified', 'local', 'authorities']
['enforcement', 'agencies', 'precautionary', 'culturally', 'tailored', 'information', 'translated']
['multiple', 'language', 'manuals', 'factual', 'regarding', 'covid', 'should', 'promoted']
['through', 'media', 'campaigns', 'evidence', 'based', 'approach', 'services']
['local', 'languages', 'mostly', 'graphic', 'pictorial', 'understanding', 'should']
['available', 'people', 'limited', 'access', 'healthcare', 'elderly', 'people', 'rural', 'areas']
['general', 'public', 'isolation', 'quarantined', 'decrease', 'covid', 'infection']
['imperative', 'bring', 'communities', 'institutional', 'leadership', 'together', 'promote']
['transparency', 'information', 'governance', 'control', 'misinfodemics', 'related']
['covid', 'people', 'physical', 'mental', 'psychosocial', 'health', 'sound', 'economic', 'political', 'systematic', 'functioning', 'during', 'pandemic', 'oliver']
['world', 'needs', 'coordinated', 'national', 'international', 'efforts', 'apply', 'scientific']
['empirical', 'local', 'settings', 'mitigate', 'grave', 'predicament', 'lockdown', 'aftereffects']
['international', 'sociology']
['associated', 'issues', 'media', 'healthcare', 'organizations', 'community', 'based', 'organizations', 'stakeholders', 'should', 'strategically', 'partnership', 'disseminate', 'based']
['mutual', 'consensus', 'empirically', 'based', 'public', 'health', 'messages', 'remove', 'science']
['online', 'content', 'through', 'natural', 'language', 'processing', 'mining', 'approaches']
['global', 'solution', 'global', 'disease', 'international', 'collaboration', 'exchange', 'scientific', 'ideas', 'health', 'communication', 'facilitating', 'coordination']
['paper']
['impact', 'covid', 'psychology', 'among', 'university']
['students']
['bablu', 'kumar', 'foster', 'ayittey', 'sabrina', 'maria', 'sarkar']
['purpose', 'study', 'psychological', 'impact']
['covid', 'pandemic', 'university', 'students', 'study', 'focuses']
['university', 'students', 'different', 'public', 'private', 'universities']
['bangladesh', 'through', 'questionnaires', 'according', 'guideline']
['generalized', 'anxiety', 'disorder', 'scale', 'result', 'among']
['respondents', 'shows', 'suffering', 'severe', 'anxiety']
['moderate', 'anxiety', 'anxiety', 'results', 'highlight']
['epidemic', 'related', 'stressors', 'positively', 'correlated', 'level']
['anxiety', 'among', 'epidemic', 'related', 'stressors', 'worry', 'about', 'economic']
['influences', 'during', 'after', 'covid', 'worry', 'about']
['influence', 'covid', 'daily', 'highly']
['positive', 'impact', 'level', 'anxiety', 'following', 'these', 'stressors', 'worry', 'about']
['academic', 'delays', 'covid', 'worry', 'about']
['social', 'support', 'during', 'covid', 'moderately']
['positively', 'correlated', 'level', 'anxiety', 'study', 'suggests', 'proper']
['government', 'support', 'social', 'awareness', 'should', 'monitored']
['during', 'epidemics', 'decreasing', 'anxiety', 'maintaining', 'mental']
['health', 'university', 'students']
['introduction']
['current', 'population', 'density', 'bangladesh']
['people', 'square', 'kilometer', 'which', 'increase']
['because', 'density', 'population', 'bangladesh']
['densely', 'populated', 'country', 'world']
['according']
['report', 'world', 'economic', 'forum', 'covid', 'threatens', 'cause', 'humanitarian', 'crisis']
['country', 'according', 'world']
['bangladesh', 'workers']
[]
['economic', 'shutdown', 'sparked', 'covid']
['endangers', 'millions', 'livelihoods', 'nently', 'people', 'could', 'their']
['daily', 'expenditures', 'their', 'children']
['school', 'expected', 'could']
['money', 'emergency', 'health', 'crisis']
['majority', 'villagers', 'depend', 'remit', 'tances', 'cities', 'overseas', 'current', 'global', 'crisis', 'people']
['income', 'halted']
['based', 'report', 'reuters']
['covid', 'pandemic', 'confirmed']
['spread', 'bangladesh', 'march']
['after', 'recognizing', 'first', 'three', 'known']
['cases', 'reported', 'march']
['institute', 'epidemiology', 'disease', 'control']
['research', 'iedcr', 'country']
['according', 'iedcr', 'bangladesh']
['level', 'infections', 'remained']
['march', 'although', 'there', 'precipitous']
['april', 'ending', 'april', 'cases', 'bangla', 'highest', 'ahead', 'indonesia']
['there', 'total', 'confirmed']
['cases', 'besides', 'recovered', 'death', 'cases']
['novel', 'coronavirus', 'covid', 'spreading', 'faster']
['country', 'current', 'situation', 'imposes', 'massive', 'government', 'bangladesh', 'general', 'public']
['healthcare', 'medical', 'providers']
['pandemic', 'brought']
['danger', 'death', 'epidemiologic', 'conta', 'intolerable', 'psychological', 'burden', 'people']
['among', 'world']
['bangladesh', 'faster', 'spread', 'virus', 'strict', 'isolation', 'measures']
['delays', 'starting', 'schools', 'colleges', 'universities', 'across']
['country', 'anticipated', 'influence', 'psychology', 'versity', 'students']
['psychological', 'reports', 'indicate', 'influence']
['epidemic', 'children', 'public', 'older', 'adults', 'medical']
['staff', 'patients']
['however', 'thorough', 'research']
['psychology', 'university', 'students', 'facing', 'epidemic']
['conducted']
['other', 'sectors', 'education', 'sector', 'affected']
['severely', 'bangladesh', 'march', 'government']
['closed', 'schools', 'colleges', 'universities', 'bangladesh']
['eight', 'confirmed', 'cases', 'among', 'students']
['universities', 'bangladesh', 'number', 'public', 'univer', 'sities', 'students', 'number', 'private']
['universities', 'students', 'average', 'student', 'count', 'public', 'university', 'private']
['university', 'indicates', 'there', 'students', 'versity', 'having', 'number', 'undergraduate', 'graduate']
['postgraduate', 'students', 'country', 'wishes', 'secure', 'future']
['temporary', 'collapsed', 'current', 'pandemic']
['detecting', 'anxiety', 'disorders', 'seven', 'generalized']
['anxiety', 'disorder', 'scale', 'extensively']
['tools', 'score', 'takes', 'finish']
['moreover', 'applicable', 'diagnosis', 'screening']
['valuation', 'strictness', 'anxiety', 'disorders']
['panic', 'disorders', 'stress', 'disorders', 'traumatic', 'disorders']
['social', 'phobia']
['prior', 'problem', 'students', 'university', 'mostly']
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['increases', 'among', 'university', 'students']
['hence', 'method']
['supervisory', 'university', 'students', 'during', 'public', 'health', 'crises']
['different', 'challenging', 'therefore', 'study', 'aimed', 'psychological', 'impact', 'covid', 'pandemic', 'among']
['university', 'students', 'bangladesh', 'moreover', 'study', 'intends']
['provide', 'suggestions', 'government', 'government']
['organizations', 'taking', 'necessary', 'steps']
['results']
['demographic', 'statistics']
['table', 'shows', 'demographic', 'particular', 'characteristics']
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[]
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[]
[]
[]
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[]
[]
[]
['1sprt']
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
['γ2ausc']
['γ2busc']
['γ3ausd']
[]
[]
[]
['1nsrt']
[]
[]
[]
['1nsrt']
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
['γ1nsrt', 'γ2ausc']
['γ2busc']
[]
[]
['γ3busd']
[]
['1ibert']
[]
[]
[]
['1ibert']
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
['γ1ibert', 'γ2aspc']
['γ2bspc']
[]
[]
['γ3bspd']
[]
['1ftmrt']
[]
[]
[]
['1ftmrt']
[]
[]
[]
['1itlc']
[]
[]
[]
[]
[]
['1itlc']
[]
[]
[]
[]
[]
['1itld']
[]
[]
[]
[]
[]
[]
['γ1ftmrt', 'γ2aitlc']
[]
[]
[]
[]
[]
[]
[]
['1daxrt']
[]
[]
[]
['1daxrt']
[]
[]
[]
['1gerc']
[]
[]
[]
[]
[]
['1gerc']
[]
[]
[]
[]
['1gerd']
[]
[]
[]
[]
[]
[]
['γ1daxrt', 'γ2agerc']
['γ2bgerc']
[]
[]
['γ3bgerd']
[]
['frontiers', 'psychology', 'frontiersin', 'september', 'volume', 'article', '1924fpsyg', '01924', 'september']
['shehzad', 'financial', 'markets', 'behavior', 'covid']
['1lsert']
[]
[]
[]
['1lsert']
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
['γ1lsert', 'γ2aukc']
['γ2bukc']
[]
[]
['γ3bukd']
[]
['ϑ2bϑ3aand', 'short', 'factors', 'while']
[]
[]
['indicates', 'parameters']
['whereas', 'symbolizes', 'number', 'model']
['based', 'akaik', 'information', 'criterion', 'schwarz', 'information']
['criterion', 'above', 'stated', 'equations', 'assumed']
['confirmed', 'number', 'cases', 'deaths', 'covid']
['asymmetrical', 'impact', 'stock', 'returns']
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
['designates', 'positive', 'shock', 'though']
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
['implies', 'negative', 'shock', 'variable']
['computed', 'follows']
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
['delineates', 'positive', 'shock', 'variable', 'denotes']
['asymmetric', 'distributive', 'error', 'correction']
['these', 'factors', 'written', 'follows']
['1sprt']
[]
[]
[]
['1sprt']
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
['φ1ectt']
['1nsrt']
[]
[]
[]
['1nsrt']
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
['φ1ectt']
['1ibert']
[]
[]
[]
['1ibert']
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
['φ1ectt']
['1ftmrt']
[]
[]
[]
['1ftmrt']
[]
[]
[]
['1itlc']
[]
[]
[]
[]
[]
['1itlc']
[]
[]
[]
[]
[]
['1itld']
[]
[]
[]
[]
[]
[]
['φ1ectt']
['1daxrt']
[]
[]
[]
['1daxrt']
[]
[]
[]
['1gerc']
[]
[]
[]
[]
[]
['1gerc']
[]
[]
[]
[]
[]
['1gerd']
[]
[]
[]
[]
[]
[]
['φ1ectt']
['1lsert']
[]
[]
[]
['1lsert']
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
['φ1ectt']
['directs', 'error', 'correction']
['cointegration', 'among', 'variables', 'examined', 'through', 'bound']
['approach', 'pesaran', 'method', 'relies', 'evaluate', 'hypothesis']
['purpose', 'pesaran', 'defined', 'bounds']
['upper', 'lower', 'bound', 'estimated', 'statistics']
['higher', 'upper', 'bound', 'limit', 'hypothesis']
['cointegration', 'rejected', 'however', 'projected', 'value', 'lower', 'lower', 'bound', 'limit', 'hypothesis', 'cannot']
['rejected', 'besides', 'value', 'remains', 'between']
['limits', 'results', 'conclusive', 'project']
['employed', 'verify', 'asymmetric']
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
['andshort']
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
[]
['asymmetric']
['relationship', 'between', 'study', 'variables']
['frontiers', 'psychology', 'frontiersin', 'september', 'volume', 'article', '1924fpsyg', '01924', 'september']
['shehzad', 'financial', 'markets', 'behavior', 'covid']
['study', 'findings']
['descriptive', 'summary', 'showed', 'table', 'during', 'covid', 'stock', 'returns', 'negative', 'further', 'skewness']
['values', 'these', 'markets', 'negative', 'except']
['kurtosis', 'which', 'predicts', 'chances', 'these']
['table', 'presents', 'results', 'augmented', 'dickey', 'fuller']
['dickey', 'fuller', 'phillip', 'perron']
['phillips', 'perron', 'showed', 'study', 'variables']
['diverse', 'stationary', 'levels', 'variable']
['cointegrated']
['bound', 'cointegration', 'fallouts']
['outcomes', 'bound', 'displayed', 'table', 'disclosed']
['significant', 'statistical', 'evidence', 'association', 'between']
['study', 'variables', 'equation', 'statistics', 'joint']
['significance', 'lagged', 'level', 'parameters', 'stated']
['respectively', 'these', 'values']
['surpass', 'upper', 'bound', 'limits', 'implying']
['cointegration', 'exists', 'among', 'economic', 'crisis', 'health']
['crisis', 'financial', 'markets', 'equation']
['short', 'asymmetric']
['cointegration', 'reckoning']
['table', 'exhibited', 'upshots', 'statistics']
['particularized', 'linear', 'association']
['however', 'revealed', 'short', 'asymmetric']
['affiliation', 'besides', 'caused', 'asymmetric']
['influence', 'short', 'periods']
['while', 'possessed', 'short', 'asymmetry', 'additionally']
['table', 'descriptive', 'statistics']
[]
['41737', '08997', '70833', '28187']
['skewness', '68003', '687765', '641313', '027343', '392073', '081854', '35422', '186996']
['kurtosis', '36907', '166164', '206693', '903565', '778953', '75376', '380136', '389965']
['jarque', '26244', '69524', '87966', '47298', '76708']
['probability', '00434', '000161']
[]
['18523', '54717', '42086', '40245']
['skewness', '927378', '53985', '120857', '230936', '65869', '232889', '058817', '31595']
['kurtosis', '43888', '59924', '573906', '120135', '135106', '868864', '472667', '04434']
['jarque', '44518', '49843', '45175', '59309', '03773', '08892']
['probability', '000013', '003185', '000121', '000872']
['source', 'author', 'calculation']
['table']
['statistics', 'statistics']
['variable', 'level', 'level']
['893713', '54426', '057616']
['293963', '969976', '971366', '51473']
['935247', '359161', '147762', '393867']
['631659', '55646', '451458']
['127702', '174362', '400067', '35456']
['300231', '849862', '488626', '372171']
['27056', '985616', '446574', '65801']
['506727', '32241', '159422', '09496']
['552953', '028486', '374729', '97616']
['775255', '591517', '768878', '87539']
['816325', '578091', '746256', '61778']
['429147', '36282', '571441', '31254']
['89506', '022076', '13962']
['847753', '567572', '310638', '46537']
['138569', '097646', '384682', '006879']
['66594', '40744', '64235', '28961']
['denote', 'level', 'significance', 'respectively', 'source', 'author', 'calculation']
['frontiers', 'psychology', 'frontiersin', 'september', 'volume', 'article', '1924fpsyg', '01924', 'september']
['shehzad', 'financial', 'markets', 'behavior', 'covid']
['table', 'results', 'bound']
['statistic', 'value', 'signif', 'statistics', 'value', 'signif']
[]
['statistic', '02410', 'statistic', '165881']
[]
[]
[]
['statistic', '11238', 'statistic', '23325']
[]
[]
[]
['statistic', '490181', 'statistic', '03259']
[]
[]
['source', 'author', 'calculation']
['table']
['asymmetry', 'short', 'asymmetry', 'asymmetry', 'short', 'asymmetry']
[]
['242605']
[]
[]
['574046']
['589403', '609162', '338933']
[]
['569179', '725822', '640751']
['61007', '786146', '718125']
['denote', 'level', 'significance', 'respectively', 'source', 'author', 'calculation']
['results', 'designated', 'asymmetric']
['relationship', 'statistics', 'enlightened']
['short', 'linear', 'impacts']
['short', 'linear', 'affiliation']
['moreover', 'denotes', 'asymmetric', 'liaison']
['hence', 'existence', 'linearity', 'study', 'variables']
['choose', 'nardl', 'model', 'computing']
['short', 'factors']
['modeling', 'nardl', 'parameters']
['linear', 'fallouts', 'presented', 'table', 'illustrated']
['expansion', 'contraction', 'brings', 'reduction']
['increase', 'respectively', 'indicates', 'strict', 'lockdown']
['substantially', 'decreases', 'market', 'returns']
['versa', 'further', 'positive', 'shock', 'caused', 'significant']
['short', 'lagged', 'values', 'specified']
['negative', 'shock', 'amplified', 'besides', 'lagged']
['terms', 'described', 'uptick', 'effect', 'improved']
['negative', 'shock', 'second', 'augmented']
['first', 'third', 'represents', 'reverse', 'impact']
['furthermore', 'negative', 'significant', 'value', 'stated']
['disequilibrium', 'occurred', 'today', 'covid']
['adjust', 'speed', 'units', 'subsequent']
['squared', 'value', 'indicated', 'volatility']
['owing', 'covid']
['model', 'results', 'exhibited', 'table', 'particularized']
['positive', 'negative', 'shocks', 'escalate']
['while', 'enlargement', 'reduction', 'instigate', 'decrease']
['increase', 'specifies', 'upsurge', 'health', 'crisis']
['expressively', 'distressed', 'nasdaq', 'composite', 'index']
['versa', 'nonetheless', 'short', 'negative', 'shock']
['demonstrated', 'imperative', 'decrease']
['whereas', 'expansion', 'lessens', 'negative']
['significant', 'parameter', 'stated', 'financial', 'instability']
['generated', 'covid', 'would', 'settled', 'speed']
['units', 'square', 'value', 'signified']
['instability', 'occurring', 'result', 'covid']
['finding', 'parameters', 'model', 'table', 'identified']
['assertive', 'shock', 'encouraging', 'effect']
['besides', 'adverse', 'shocks', 'remain', 'insignificant', 'other']
['escalation', 'decline', 'negative', 'positive', 'influence']
['implying', 'strict', 'lockdown', 'considerably', 'caused']
['financial', 'crisis', 'spain', 'period', 'short']
['period', 'intensification', 'decline']
['increased', 'negative', 'significant', 'value']
['elucidated', 'today', 'disequilibrium', 'adjust']
['speed', 'units', 'coefficient', 'square']
['stated', 'variations', 'owing', 'covid']
['table', 'displayed', 'fallouts', 'stock', 'market']
['condition', 'covid', 'italy', 'stock', 'markets', 'exposed']
['frontiers', 'psychology', 'frontiersin', 'september', 'volume', 'article', '1924fpsyg', '01924', 'september']
['shehzad', 'financial', 'markets', 'behavior', 'covid']
['table', 'asymmetric', 'parameters']
['variables', 'short', 'coefficients', 'error']
['usc_neg', '047867', '003539', '52394']
['usc_neg', '061323', '003402', '02596']
['usc_neg', '108895', '005569', '55339']
['usc_neg', '072915', '003619', '14618']
['usd_pos', '713848', '036514', '55011']
['usd_pos', '23431', '014268', '42276']
['usd_pos', '194744', '01369', '22562']
['usd_pos', '334891', '029691', '27907']
['usd_neg', '377433', '055371', '816426']
['usd_neg', '65514', '097958', '89641']
['usd_neg', '074692', '02737', '728986']
['usd_neg', '650475', '235321', '51275']
['369525', '066813', '49782']
['squared', '912909']
['adjusted', 'squared', '892007']
['durbin', 'watson', '006439']
['variables', 'coefficients', 'error']
['usc_pos', '004491', '001667', '694157']
['usc_neg', '054381', '014406', '774912']
['usd_pos', '064436', '029631', '174626']
['usd_neg', '290139', '338048', '858278']
['181416', '264851', '684971']
['denote', 'level', 'significance', 'respectively', 'source', 'author', 'calculation']
['table', 'asymmetric', 'parameters']
['variables', 'short', 'coefficients', 'error']
['usd_neg', '039324', '019503', '016267']
['usc_pos', '002147', '000382', '622014']
['usc_neg', '002319', '00069', '360414']
['usc_neg', '008198', '001064', '703282']
['501702', '093855', '00026']
['squared', '812596']
['adjusted', 'squared', '800102']
['durbin', 'watson', '130245']
['variables', 'coefficients', 'error']
['usd_pos', '013042', '004465', '920922']
['usd_neg', '026413', '030567', '864107']
['usc_pos', '001013', '00034', '977381']
['usc_neg', '004258', '001923', '214416']
['525513', '274541', '914153']
['denote', 'level', 'significance', 'respectively', 'source', 'author', 'calculation']
['reduction', 'diminished', 'amplified']
['inferring', 'heath', 'crisis', 'imperatively', 'contributes', 'italy']
['financial', 'instability', 'period', 'addition', 'growth']
['enlarged', 'imperatively', 'condition']
['italy', 'denoted', 'first', 'second', 'third', 'values']
['harmed', 'returns', 'growth', 'negative']
['impression', 'nonetheless', 'negative', 'shock']
['second', 'value', 'indicated', 'encouraging', 'effect']
['consequences', 'symbolized', 'proliferation']
['possess', 'negative', 'ftmer', 'first']
['second', 'value', 'definite', 'furthermore', 'decline']
['direct', 'influence', 'negative']
['significant', 'figure', 'itemized', 'readjust']
['equilibrium', 'speed', 'units', 'squared', 'parameter', 'denoted', 'uncertainty', 'generated']
['caused', 'covid']
['frontiers', 'psychology', 'frontiersin', 'september', 'volume', 'article', '1924fpsyg', '01924', 'september']
['shehzad', 'financial', 'markets', 'behavior', 'covid']
['table', 'asymmetric', 'parameters']
['variables', 'short', 'coefficients', 'error']
['368944', '09522']
['spd_pos', '018471', '009268']
['spd_neg', '026216', '010675']
['spc_pos', '001511', '000911']
['spc_neg', '001832', '000966']
['spc_neg', '00301', '000996']
['spc_neg', '006948', '00129']
['824331', '137511']
['squared', '726141']
['adjusted', 'squared', '694191']
['durbin', 'watson', '154368']
['variables', 'coefficients', 'error']
['spd_pos', '053991', '01765']
['spd_neg', '023488', '018017']
['spc_pos', '006341', '001968']
['spc_neg', '005173', '001945']
['636028', '428132']
['denote', 'level', 'significance', 'respectively', 'source', 'author', 'calculation']
['table', 'asymmetric', 'parameters']
['variables', 'short', 'coefficients', 'error']
['27947', '138377', '019624']
['154875', '136743', '132605']
['295127', '113398', '602569']
['itlc_pos', '008711', '001397', '235569']
['itlc_pos', '015154', '003264', '642728']
['itlc_pos', '002589', '573306']
['itlc_neg', '001115', '001937', '575378']
['itlc_neg', '006885', '00198', '477965']
['itlc_neg', '003758', '001782', '109409']
['itld_pos', '06983', '014714', '745672']
['itld_pos', '023801', '011962', '989722']
['itld_pos', '029575', '010511', '813763']
['itld_neg', '002565', '012862', '199404']
['itld_neg', '038093', '015194', '507186']
['itld_neg', '04502', '013664', '294772']
['959373', '163657', '862111']
['squared', '851016']
['adjusted', 'squared', '807197']
['durbin', 'watson', '763297']
['variables', 'coefficients', 'error']
['itlc_pos', '013317', '005649', '357295']
['itlc_neg', '001321', '002682', '492464']
['itld_pos', '109433', '053273', '054209']
['itld_neg', '048345', '020559', '351573']
['500777', '455916', '098396']
['denote', 'level', 'significance', 'respectively', 'source', 'author', 'calculation']
['parameters', 'table', 'directed']
['upsurge', 'diminution', 'compacted']
['enlarge', 'moreover', 'decline']
['improves', 'these', 'findings', 'revealed', 'lockdown']
['health', 'crises', 'harmful', 'stock', 'markets']
['germany', 'short', 'findings', 'described', 'second']
['frontiers', 'psychology', 'frontiersin', 'september', 'volume', 'article', '1924fpsyg', '01924', 'september']
['shehzad', 'financial', 'markets', 'behavior', 'covid']
['table', 'asymmetric', 'parameters']
['variables', 'short', 'coefficients', 'error']
['gerc_pos', '015476', '001209', '80122']
['gerc_pos', '012439', '001923', '467043']
['gerc_pos', '088025', '005402', '29596']
['gerc_pos', '057992', '003854', '04828']
['gerc_pos', '00647', '99249']
['gerc_neg', '05202', '004721', '11903']
['gerc_neg', '067796', '004325', '67443']
['gerc_neg', '044564', '003649', '21376']
['gerc_neg', '01327', '004158', '191441']
['gerc_neg', '183056', '01145', '98705']
['gerd_pos', '101477', '313432', '27619']
['gerd_pos', '265597', '35462', '84858']
['gerd_pos', '054459', '100825', '540134']
['gerd_pos', '261756', '386781', '18939']
['gerd_neg', '913296', '288936', '54383']
['gerd_neg', '64757', '850055', '56576']
['gerd_neg', '76795', '466544', '20677']
['gerd_neg', '21192', '08761']
['497359', '029762', '71134']
['squared', '945788']
['adjusted', 'squared', '910937']
['durbin', 'watson', '667758']
['variables', 'coefficients', 'error']
['gerc_pos', '016748', '035958', '465776']
['gerc_neg', '255912', '083972']
['gerd_pos', '28734', '569148', '548151']
['gerd_neg', '49979', '581496']
['440744', '93232', '617925']
['denote', 'level', 'significance', 'respectively', 'source', 'author', 'calculation']
['table', 'asymmetric', 'parameters']
['variables', 'short', 'coefficients', 'error']
['ukc_pos', '00127', '001661', '764723']
['ukc_pos', '022345', '003248', '878603']
['ukc_neg', '009267', '002137', '337228']
['ukd_pos', '03503', '00746', '695883']
['ukd_pos', '090212', '014812', '090388']
['100754', '115104', '563147']
['squared', '651816']
['adjusted', 'squared', '624182']
['durbin', 'watson', '867108']
['variables', 'coefficients', 'error']
['ukc_pos', '003609', '00191', '889866']
['ukc_neg', '003213', '002112', '521044']
['ukd_pos', '075038', '02864', '620078']
['ukd_neg', '086022', '035056', '453823']
['319529', '353596', '903654']
['denote', 'level', 'significance', 'respectively', 'source', 'author', 'calculation']
['third', 'fourth', 'positive', 'shocks']
['lessening', 'impact', 'however', 'negative', 'shock']
['other', 'values', 'except', 'first', 'indicated']
['indirect', 'association', 'additionally', 'positive']
['shocks', 'quantified', 'mixed', 'impact']
['while', 'short', 'decline', 'negative', 'first']
['frontiers', 'psychology', 'frontiersin', 'september', 'volume', 'article', '1924fpsyg', '01924', 'september']
['shehzad', 'financial', 'markets', 'behavior', 'covid']
['second', 'third', 'values', 'point', 'positive']
['linkage', 'these', 'effects', 'because', 'instability']
['generated', 'covid', 'squared', 'coefficient']
['diagnosed', 'instability', 'because']
['covid']
['table', 'represents', 'results', 'london', 'stock']
['exchange', 'concluding', 'coefficients', 'explored']
['augmentation', 'improved', 'while', 'diminution']
['reduces', 'period', 'although']
['growth', 'brought', 'significant', 'decrease']
['short', 'period', 'outlined', 'positive', 'shocks']
['reduced', 'first', 'value', 'positive', 'shock']
['showed', 'alternate', 'impression', 'additionally']
['upturn', 'possesses', 'diminishing', 'impact']
['these', 'outcomes', 'designated', 'lockdown', 'health', 'crises']
['generated', 'covid', 'negatively', 'impact', 'financial']
['markets', 'short', 'period', 'value']
['showed', 'fluxes', 'occurred', 'today']
['equilibrium', 'speed', 'units']
['square', 'value', 'reported', 'variation']
['covid', 'figure', 'depicts', 'adjustment', 'asymmetric']
['effect', 'existing', 'equilibrium', 'moved']
['equilibrium', 'result', 'positive', 'adverse']
['shocks', 'asymmetric', 'plots', 'denote', 'alliance', 'dynamic']
['multipliers', 'owing', 'positive', 'adverse', 'shocks']
['nasdaq', 'composite', 'index']
['markets', 'outcomes', 'revealed', 'these', 'markets', 'tremendously']
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['three', 'authors', 'grouped', 'similar', 'keywords', 'together', 'mapped', 'groups', 'keywords', 'language']
['categories', 'grouping', 'mapping', 'procedure', 'informed', 'previous', 'studies', 'investigated', 'these']
['keywords', 'expressed', 'through', 'language', 'these', 'studies', 'listed', 'table']
['language', 'categories', 'considered', 'tweet', 'contained', 'language', 'category', 'least']
['tweet', 'words', 'stems', 'belonged', 'category', 'tweet', 'category', 'association', 'binary', 'disregards']
['number', 'matching', 'words', 'within', 'tweet', 'mainly', 'because', 'short', 'snippets', 'tweets']
['limited', 'characters', 'multiple', 'occurrences', 'necessarily', 'reflect', 'intensity', 'egory', 'russell', 'language', 'category', 'counted', 'number', 'users', 'posted', 'least']
['tweet', 'containing', 'category', 'obtained', 'fraction', 'users', 'mentioned', 'category']
['dividing', 'total', 'number', 'users', 'tweeted']
[]
[]
[]
['computing', 'fraction', 'users', 'rather', 'fraction', 'tweets', 'prevents', 'biases', 'introduced', 'exceptionally', 'active']
['users', 'capturing', 'faithfully', 'prevalence', 'different', 'language', 'categories', 'twitter', 'population']
['helps', 'discounting', 'impact', 'social', 'which', 'anomalous', 'levels', 'activity', 'especially']
['retweeting', 'bessi', 'ferrara']
['different', 'categories', 'might', 'verbalized', 'considerably', 'different', 'frequencies', 'example', 'language', 'category']
['first', 'person', 'pronoun', 'lexicon', 'naturally', 'occurred', 'frequently', 'category']
['death', 'lexicon', 'enable', 'comparison', 'across', 'categories', 'standardized', 'fractions']
[]
[]
[]
['where', 'represent', 'standard', 'deviation', 'scores', 'whole', 'period']
['february', 'april', 'these', 'scores', 'interpretation', 'results']
['represent', 'relative', 'variation', 'category', 'prevalence', 'compared', 'average', 'values', 'higher']
['lower', 'original', 'value', 'higher', 'lower', 'average']
['other', 'behavioral', 'markers', 'assess', 'validity', 'operationalization', 'strong', 'model', 'compared']
['results', 'output', 'alternative', 'state', 'mining', 'techniques', 'world', 'mobility', 'patterns']
['interaction', 'types', 'compared', 'results', 'obtained', 'matching', 'state', 'learning']
['natural', 'language', 'processing', 'designed', 'capture', 'fundamental', 'types', 'social', 'interactions', 'conversational']
['language', 'short', 'memory', 'neural', 'networks', 'lstms', 'hochreiter']
['schmidhuber', 'input', 'dimensional', 'glove', 'representation', 'words', 'pennington']
['output', 'series', 'confidence', 'scores', 'range', 'estimate', 'likelihood', 'expresses', 'certain']
['types', 'social', 'interactions', 'classifiers', 'exhibited', 'classification', 'performance', 'under']
['curve', 'performance', 'metric', 'measures', 'ability', 'model', 'assign']
['higher', 'confidence', 'scores', 'positive', 'examples', 'characterized', 'interaction', 'interest']
['negative', 'examples', 'independent', 'fixed', 'decision', 'threshold', 'expected', 'value', 'random', 'classification']
['whereas', 'indicates', 'perfect', 'classification']
['interaction', 'types', 'classify', 'three', 'detected', 'frequently']
['likelihood', 'twitter', 'conflict', 'expressions', 'contrast', 'diverging', 'views', 'tajfel', 'social']
['support', 'giving', 'emotional', 'practical', 'companionship', 'fiske', 'power', 'expressions']
['person', 'power', 'behavior', 'outcomes', 'another']
['given', 'tweet', 'textual', 'message', 'interaction', 'classifier', 'compute', 'likelihood']
['score', 'message', 'contains', 'interaction', 'binarized', 'confidence', 'scores', 'using']
['threshold', 'based', 'indicator', 'function']
[]
[]
[]
[]
[]
['otherwise']
['following', 'original', 'approach', 'different', 'threshold', 'interaction']
['distributions', 'their', 'likelihood', 'scores', 'considerably', 'picked', 'conservatively', 'value']
['percentile', 'distribution', 'confidence', 'scores']
['favoring', 'precision', 'recall', 'similar', 'tohow', 'epidemic', 'psychology', 'works', 'twitter']
[]
['keywords', 'supporting', 'literature', 'categories']
[]
[]
[]
['emotional', 'maelstrom', 'swear']
['anger']
['negemo']
['these', 'categories', 'analyze']
['complex', 'emotional', 'responses', 'traumatic', 'events']
['characterize', 'language', 'people']
['suffering', 'mental', 'health', 'coppersmith']
['sadness']
['related', 'words', 'included', 'emolex']
['often', 'measure', 'tangible']
['intangible', 'threats']
['emolex']
['death']
['anxiety', 'panic', 'anxiety', 'category', 'study', 'ferent', 'forms', 'anxiety', 'social', 'media', 'rudzicz']
[]
['anxiety']
['disorientation', 'definition', 'tentative', 'category', 'expresses']
['uncertainty', 'tausczik', 'pennebaker']
['tentative']
['suspicion', 'suspicion', 'often', 'formalized', 'trust', 'deutsch']
[]
['trust']
['irrationality', 'negate', 'category', 'measure']
['cognitive', 'distorsions', 'irrational', 'interpretations', 'ality', 'simms']
['negate']
['religion', 'religious', 'expressions', 'study']
['people', 'appeal', 'religious', 'entities', 'during', 'moments']
['hardship']
['religion']
['contagion', 'these', 'categories', 'study']
['perception', 'diseases', 'cancer', 'support', 'groups', 'people']
['affected', 'eating', 'disorder', 'alcoholics', 'alpers']
['kornfield']
[]
[]
['moralization']
['avoidance']
['perception']
['category', 'model', 'perception', 'connected']
['epidemics']
[]
['polarization', 'segregation', 'different', 'personal', 'pronouns', 'study', 'group', 'dynamics', 'characterize', 'language']
['markers', 'racism', 'arguello', 'personal']
['pronouns', 'markers', 'differentiation']
['considered', 'studies', 'racist', 'language', 'figea']
[]
[]
[]
[]
['differ']
['stigmatization', 'blame']
['abuse']
['pronouns', 'quantify', 'blame']
['personal', 'borelli', 'sbarra', 'political', 'windsor', 'speech', 'associated']
['oriented', 'statements', 'elsherief']
['categories']
['previous']
['cooperation']
['coordination', 'collective']
['consciousness']
['moral', 'value', 'expresses', 'protecting']
['others', 'graham', 'cooperation', 'often']
['verbalized', 'referencing', 'group', 'expressing']
['affiliation', 'rezapour']
['affiliation']
['moral', 'virtue']
['prosocial', 'prosocial']
['faith', 'authority', 'moral', 'value', 'authority', 'expresses', 'playing']
['rules', 'hierarchy', 'versus', 'challenging', 'rezapour']
[]
['authority', 'moral']
['virtue']
[]
['authority', 'enforcement', 'power', 'category', 'expresses', 'exertion', 'inance', 'tausczik', 'pennebaker']
['power']
['action']
['restrictions', 'travel']
['motion']
[]
[]
['social']
['daily', 'habits', 'concern', 'mainly', 'people', 'experience']
['leisure', 'movement', 'between']
['gonzalez']
['leisure']
['table', 'operationalization', 'strong', 'epidemic', 'psychology', 'theoretical', 'framework', 'strong', 'paper']
['three', 'annotators', 'extracted', 'keywords', 'characterize', 'three', 'psycho', 'social', 'epidemics', 'mapped']
['relevant', 'language', 'categories', 'existing', 'language', 'lexicons', 'psychometric', 'studies', 'category', 'names']
['followed', 'their', 'corresponding', 'lexicon', 'parenthesis', 'support', 'association', 'between', 'keywords']
['language', 'categories', 'examples', 'supporting', 'literature', 'summarize', 'language', 'egories', 'varies', 'across', 'three', 'temporal', 'states', 'computed', 'values', 'different', 'language', 'categories']
['their', 'standardized', 'fractions', 'reached', 'maximum', 'reported', 'percentage', 'increase']
['compared', 'average', 'whole', 'period', 'maximum', 'value', 'highlighted', 'epidemic', 'psychology', 'works', 'twitter']
['constructed', 'temporal', 'signals', 'language', 'categories', 'counted', 'number', 'users', 'posted']
['least', 'tweet', 'contains', 'interaction', 'obtained', 'fraction', 'users', 'mentioned']
['interaction', 'dividing', 'total', 'number', 'users', 'tweeted']
[]
[]
[]
['normalized', 'these', 'fractions', 'considering', 'minimum', 'maximum', 'values', 'during', 'whole']
['period']
[]
[]
[]
['mentions', 'medical', 'entities', 'state', 'learning', 'method', 'medical', 'entity', 'extraction']
['identify', 'medical', 'symptoms', 'twitter', 'relation', 'covid', 'scepanovic', 'applied', 'tweets']
['method', 'extracts', 'grams', 'representing', 'medical', 'symptoms', 'feeling', 'method', 'based']
['sequence', 'tagging', 'architecture', 'huang', 'combination', 'glove', 'embeddings', 'nington', 'roberta', 'contextual', 'embeddings', 'optimize', 'entity', 'extraction']
['performance', 'noisy', 'textual', 'social', 'media', 'trained', 'sequence', 'tagging', 'architecture', 'micromed']
['database', 'jimeno', 'yepes', 'collection', 'tweets', 'manually', 'labeled', 'medical', 'entities', 'hyper', 'parameters', 'hidden', 'units', 'batch', 'learning', 'which', 'gradually', 'halved']
['whenever', 'there', 'performance', 'improvement', 'after', 'epochs', 'trained', 'maximum', 'epochs']
['before', 'learning', 'became', 'small', 'final', 'model', 'achieved', 'score', 'micromed']
['score', 'performance', 'measure', 'combines', 'precision', 'fraction', 'extracted', 'entities', 'actually']
['medical', 'entities', 'recall', 'fraction', 'medical', 'entities', 'present', 'method', 'retrieve']
['based', 'implementation', 'flair', 'akbik', 'pytorch', 'paszke', 'popular']
['learning', 'libraries', 'python']
['unique', 'medical', 'entity', 'counted', 'number', 'users', 'posted', 'least', 'tweet']
['mentioned', 'entity', 'obtained', 'fraction', 'users', 'mentioned', 'medical', 'entity', 'dividing']
['total', 'number', 'users', 'tweeted']
[]
[]
[]
['normalize', 'these', 'fractions', 'considering', 'minimum', 'maximum', 'values', 'during', 'whole']
['period']
[]
[]
[]
['mobility', 'traces', 'foursquare', 'local', 'search', 'discovery', 'mobile', 'application', 'relies', 'users', 'mobility']
['records', 'recommend', 'places', 'might', 'application', 'localization', 'estimate']
['position', 'infer', 'places', 'visited', 'response', 'covid', 'crisis', 'foursquare', 'publicly']
['available', 'gathered', 'million', 'users', 'these', 'users', 'always', 'during', 'period']
['collection', 'meaning', 'allowed', 'application', 'gather', 'location', 'times']
['application', 'published', 'through', 'visitdata', 'website', 'consists', 'daily', 'number']
['users', 'visiting', 'venue', 'state', 'starting', 'february', 'present']
['users', 'visited', 'schools', 'indiana', 'february', 'overall', 'distinct', 'location', 'categories', 'provided', 'obtain']
['country', 'temporal', 'indicators', 'first', 'applied', 'normalization', 'values']
[]
[]
[]
['averaged', 'values', 'across', 'states']
[]
[]
[]
[]
[]
['where', 'total', 'number', 'states', 'weighting', 'state', 'equally', 'obtained', 'measure']
['representative', 'whole', 'territory', 'rather', 'being', 'biased', 'towards', 'density', 'regions', 'epidemic', 'psychology', 'works', 'twitter']
['series', 'smoothing', 'temporal', 'indicators', 'affected', 'large', 'fluctuations', 'extract']
['consistent', 'trends', 'series', 'applied', 'smoothing', 'function', 'common', 'practice', 'analyzing']
['temporal', 'extracted', 'social', 'media', 'connor', 'given', 'varying', 'signal', 'apply']
['boxcar', 'moving', 'average', 'window', 'previous']
[]
[]
[]
[]
[]
[]
[]
[]
['selected', 'window', 'weekly', 'windows', 'typically', 'smooth']
['variations', 'weekly', 'periodicities', 'connor', 'applied', 'smoothing', 'series']
['language', 'categories']
[]
[]
['mentions', 'medical', 'entities']
[]
[]
['interaction', 'types']
[]
[]
[]
['foursquare', 'visits']
[]
[]
[]
['change', 'point', 'detection', 'identify', 'phases', 'characterized', 'different', 'combinations', 'language', 'categories']
['identified', 'change', 'points', 'periods', 'which', 'values', 'categories', 'varied', 'considerably', 'quantify']
['variations', 'language', 'category', 'computed']
[]
[]
['namely', 'daily', 'average', 'squared', 'gradi', 'utkepohl', 'smoothed', 'standardized', 'fractions', 'category', 'calculate', 'gradient']
['python', 'function', 'numpy', 'gradient', 'gradient', 'provides', 'measure', 'increase', 'decrease']
['signal', 'consider', 'absolute', 'value', 'gradient', 'account', 'magnitude', 'change', 'rather', 'direc', 'change', 'identify', 'periods', 'consistent', 'change', 'opposed', 'quick', 'instantaneous', 'shifts', 'apply', 'temporal']
['smoothing', 'equation', 'series', 'gradients', 'denote', 'smoothed', 'squared', 'gradients']
[]
['average', 'gradients', 'language', 'categories', 'obtain', 'overall', 'gradient']
[]
[]
[]
[]
[]
[]
[]
[]
[]
['peaks', 'series', 'represent', 'highest', 'variation', 'marked', 'change', 'points', 'using']
['python', 'function', 'scipy', 'signal', 'peaks', 'identified', 'peaks', 'local', 'maxima', 'whose', 'values', 'higher']
['average', 'standard', 'deviations', 'common', 'practice', 'palshikar']
['results']
['language', 'until', 'first', 'contagion', 'during', 'first', 'residents', 'experienced']
['pandemic', 'entailed', 'first', 'going', 'through', 'entire', 'cycle', 'making', 'contagion']
['contained', 'arrival', 'unknown', 'virus', 'skepticism', 'isolation', 'measures', 'first', 'reopening']
['figure', 'shows', 'standardized', 'fractions', 'language', 'categories', 'formula', 'changed']
['february', 'april', 'which', 'restrictions', 'states', 'lifted', 'color', 'encodes', 'values']
['higher', 'average', 'lower', 'partitioned', 'language', 'categories', 'according', 'three']
['psycho', 'social', 'epidemics', 'figure', 'shows', 'value', 'average', 'squared', 'gradient', 'formula']
['peaks', 'curve', 'represent', 'local', 'variation', 'marked', 'peaks', 'above', 'standard', 'deviations']
['change', 'points', 'found', 'change', 'points', 'coincide', 'events', 'february']
[]
['announcement', 'first', 'infection', 'country', 'march', 'announcement']
['orders', 'these', 'change', 'points', 'identify', 'three', 'phases', 'which', 'described', 'dwelling']
['peaks', 'different', 'language', 'categories', 'their', 'standardized', 'fractions', 'reached', 'maximum']
['reporting', 'percentage', 'increase', 'increase', 'compared', 'average', 'february', 'april']
[]
['denoted', 'table', 'first', 'phase', 'refusal', 'phase', 'characterized', 'anxiety']
['death', 'frequently', 'mentioned', 'february', 'compared', 'average', 'during']
['whole', 'period', 'pronoun', 'temporal', 'state', 'average', 'suggests']
['focus', 'discussion', 'implications', 'viral', 'epidemic', 'others', 'infection']
['discovered', 'other', 'language', 'categories', 'exhibited', 'significant', 'variations', 'which', 'reflected']
['overall', 'situation', 'business', 'usual']
['second', 'phase', 'anger', 'phase', 'began', 'february', 'outburst', 'negative', 'emotions', 'predominantly']
['anger', 'right', 'after', 'first', 'covid', 'contagion', 'announced', 'abstract', 'death', 'replaced']
['expressions', 'concrete', 'health', 'concerns', 'words', 'expressing', 'mentions', 'parts']
['march', 'federal', 'government', 'announced', 'state', 'national', 'emergency', 'followed', 'enforcement']
['state', 'level', 'orders', 'during', 'those', 'observed', 'sharp', 'increase', 'pronoun']
['swear', 'words', 'march', 'which', 'hints', 'climate', 'discussion', 'characterized']
['conflict', 'polarization', 'observed', 'increase', 'words', 'related', 'daily', 'habits']
['affected', 'impending', 'restriction', 'policies', 'motion', 'social', 'activities', 'leisure', 'mentions', 'words8', 'epidemic', 'psychology', 'works', 'twitter']
[]
['death']
['anxiety']
['negemo']
['anger']
['swear']
['tentative']
['negate']
[]
[]
['religion']
['posemo']
['sadness']
['trust']
[]
['refusal', 'phase', 'anger', 'phase', 'acceptance', 'phase']
[]
[]
[]
['differ']
[]
[]
['affiliation']
['authority']
['power']
[]
['prosocial']
['morality']
['focus', 'focus', 'focus']
[]
['motion']
[]
['social']
['leisure']
['action']
[]
['usual', 'beyond']
[]
[]
['gradient']
[]
[]
[]
[]
['custom', 'words']
[]
['alcohol', 'exercising', 'economic']
[]
[]
[]
['interactions']
[]
['support', 'power', 'conflict']
[]
[]
[]
['medical']
[]
['physical', 'health', 'mental', 'health']
[]
[]
[]
[]
['mobility']
[]
['first']
[]
[]
[]
['grocery', 'travel', 'transport', 'outdoors', 'recreation']
[]
[]
[]
[]
['figure', 'epidemic', 'psychology', 'twitter', 'during', 'first', 'contagion', 'evolution']
['different', 'language', 'categories', 'tweets', 'related', 'covid', 'heatmaps', 'represents']
['language', 'category', 'words', 'expressing', 'anxiety', 'manual', 'coding', 'associated', 'three']
['psycho', 'social', 'epidemics', 'color', 'represents', 'daily', 'standardized', 'fraction', 'people', 'words', 'related']
['category', 'values', 'higher', 'average', 'those', 'lower', 'categories']
['partitioned', 'three', 'groups', 'according', 'psycho', 'social', 'epidemics', 'model', 'morality', 'action']
['average', 'gradient', 'instantaneous', 'variation', 'language', 'categories', 'peaks', 'gradient', 'identify']
['change', 'points', 'dates', 'around', 'which', 'considerable', 'change', 'multiple', 'language', 'categories', 'happened']
['dashed', 'vertical', 'lines', 'cross', 'plots', 'represent', 'these', 'change', 'points', 'temporal', 'evolution']
['families', 'indicators', 'corroborate', 'validity', 'trends', 'identified', 'language', 'categories']
['checked', 'internal', 'validity', 'comparing', 'language', 'categories', 'custom', 'keyword', 'search', 'approach']
['learning', 'tools', 'extract', 'types', 'social', 'interactions', 'mentions', 'medical', 'symptoms']
['checked', 'external', 'validity', 'looking', 'mobility', 'patterns', 'different', 'venue', 'categories', 'estimated']
['localization', 'service', 'foursquare', 'mobile', 'timeline', 'bottom', 'figure', 'marks']
['events', 'covid', 'pandemic', 'announcements', 'first', 'infection', 'covid']
['recorded', 'epidemic', 'psychology', 'works', 'twitter']
['related', 'peaked', 'march', 'federal', 'government', 'announced', 'social', 'distancing']
['guidelines', 'place', 'least', 'weeks']
['third', 'phase', 'acceptance', 'phase', 'started', 'march', 'after', 'first', 'physical', 'distancing', 'measures']
['imposed', 'increased', 'words', 'power', 'authority', 'likely', 'reflected', 'emergence', 'discussion']
['around', 'policies', 'enforced', 'government', 'officials', 'public', 'agencies', 'death', 'raised', 'steadily']
['hitting', 'deaths', 'march', 'expressions', 'conflict', 'faded', 'words', 'sadness', 'became']
['predominant', 'those', 'hardship', 'sentiment', 'others', 'expressions', 'prosocial', 'behavior', 'became']
['frequent', 'respectively', 'mentions', 'related', 'activities', 'peaked', 'people']
['either', 'their', 'compelled', 'result', 'lockdown']
['thematic', 'analysis', 'language', 'categories', 'capture', 'broad', 'concepts', 'related', 'strong', 'epidemic', 'psychology']
['theory', 'allow', 'analysis', 'grained', 'topics', 'within', 'category', 'study']
['combinations', 'language', 'category', 'phase', 'language', 'categories', 'phases', 'listed']
['retweeted', 'tweets', 'popular', 'tweets', 'containing', 'anxiety', 'posted', 'refusal', 'phase']
['identify', 'overarching', 'themes', 'followed', 'steps', 'commonly', 'adopted', 'thematic', 'analysis', 'braun']
['clarke', 'smith', 'shinebourne', 'first', 'applied', 'coding', 'identify', 'concepts', 'emerged']
['across', 'multiple', 'tweets', 'specifically', 'authors', 'tweets', 'marked', 'keywords']
['reflected', 'concepts', 'expressed', 'axial', 'coding', 'identify', 'relationships', 'between']
['frequent', 'keywords', 'summarize', 'semantically', 'cohesive', 'themes', 'themes', 'reviewed', 'recursive']
['manner', 'rather', 'linear', 'evaluating', 'adjusting', 'tweets', 'parsed', 'table', 'summarizes']
['recurring', 'themes', 'together', 'their', 'representative', 'tweets', 'refusal', 'phase', 'statements']
['skepticism', 'tweeted', 'widely', 'table', 'epidemic', 'frequently', 'depicted', 'foreign', 'problem']
['activities', 'business', 'usual']
['anger', 'phase', 'discussion', 'characterized', 'outrage', 'against', 'three', 'categories', 'foreigners', 'especially']
['chinese', 'individuals', 'supplementary', 'materials', 'detail', 'political', 'opponents', 'people', 'adopted']
['different', 'behavioral', 'responses', 'outbreak', 'level', 'conflict', 'corroborates', 'strong', 'postulate']
['against', 'other', 'science', 'religion', 'prominent', 'topics', 'discussion', 'lively', 'debate', 'raged']
['around', 'validity', 'scientists', 'recommendations', 'social', 'groups', 'their', 'hopes', 'rather']
['science', 'mentions', 'people', 'isolating', 'became', 'frequent', 'highlighted', 'contrast']
['between', 'judicious', 'individuals', 'careless', 'crowds']
['finally', 'during', 'acceptance', 'phase', 'outburst', 'anger', 'sorrow', 'caused', 'mourning']
['thousands', 'people', 'accepting', 'threat', 'virus', 'twitter', 'users']
['collective', 'solutions', 'problem', 'overcome', 'although', 'positive', 'attitude', 'towards']
['authorities', 'seemed', 'prevalent', 'users', 'expressed', 'disappointment', 'against', 'restrictions', 'imposed']
['those', 'isolated', 'started', 'imagining', 'beyond', 'isolation', 'especially', 'relation', 'reopening']
['businesses']
['comparison', 'other', 'behavioral', 'markers', 'assess', 'validity', 'approach', 'compared', 'previous']
['results', 'output', 'alternative', 'mining', 'techniques', 'applied', 'internal', 'validity']
['world', 'mobility', 'traces', 'external', 'validity']
['comparison', 'other', 'mining', 'techniques', 'processed', 'social', 'media', 'posts', 'three', 'alternative']
['mining', 'techniques', 'figure', 'table', 'reported', 'three', 'language', 'categories', 'strongest']
['correlations', 'behavioral', 'marker']
['first', 'allow', 'interpretable', 'explainable', 'results', 'applied', 'simple', 'matching', 'method', 'relies']
['custom', 'lexicon', 'containing', 'three', 'categories', 'words', 'reflecting', 'consumption', 'alcohol', 'physical', 'exercising']
['economic', 'concerns', 'those', 'aspects', 'found', 'characterize', 'covid', 'pandemic', 'economist']
['measured', 'daily', 'fraction', 'users', 'mentioning', 'words', 'those', 'categories', 'figure']
['refusal', 'phase', 'frequency', 'these', 'words', 'significantly', 'increase', 'anger', 'phase', 'frequency']
['words', 'related', 'economy', 'peaked', 'related', 'alcohol', 'consumption', 'peaked', 'shortly', 'after', 'table']
['shows', 'economy', 'related', 'words', 'highly', 'correlated', 'anxiety', 'words', 'which']
['studies', 'indicating', 'degree', 'apprehension', 'declining', 'economy', 'comparable']
['health', 'hazard', 'concerns', 'fetzer', 'bareket', 'bojmel', 'words', 'alcohol', 'consumption']
['correlated', 'language', 'dimensions', 'period']
['health', 'concerns', 'their', 'isolation', 'caused', 'rising', 'alcohol', 'finlay']
['gilmore', 'finally', 'acceptance', 'phase', 'frequency', 'words', 'related', 'physical', 'exercise', 'significant', 'epidemic', 'psychology', 'works', 'twitter']
['theme', 'example', 'tweets']
['refusal', 'phase']
['denial', 'cases', 'result', 'death', 'approximately', 'equivalent', 'seasonal', 'relax']
['people']
['focus', 'continue', 'wuhanvirus', 'which', 'exactly']
['business', 'usual', 'agriculture', 'specialists', 'dulles', 'airport', 'continue', 'protect', 'nation', 'vital', 'agricultural']
['resources']
['anger', 'phase']
['anger', 'foreign']
['there', 'anything', 'hatred', 'against', 'foreigner', 'covid19']
['global', 'pandemic']
['anger', 'political']
['opponents']
['level', 'sickness', 'entered', 'politic', 'monster', 'mouthing']
['grotesque', 'about', 'cheering', 'coronavirus', 'street', 'crashing', 'because']
['father', 'winning', 'streak']
['anger']
['other']
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[]
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[]
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['human', 'factors', 'computing', 'systems', 'pages']
['bagnoli', 'sguanci', 'perception', 'epidemic', 'modeling', 'physical', 'review', '061904']
['bansal', 'chowell', 'simonsen', 'vespignani', 'viboud', 'infectious', 'disease', 'surveillance']
['modeling', 'journal', 'infectious', 'diseases', 'suppl']
['bareket', 'bojmel', 'shahar', 'margalit', 'covid', 'related', 'economic', 'anxiety', 'health', 'anxiety']
['findings', 'israel', 'international', 'journal', 'cognitive', 'therapy']
['baronchelli', 'emergence', 'consensus', 'primer', 'royal', 'society', 'science', '172189']
['bauch', 'galvani', 'social', 'factors', 'epidemiology', 'science']
['bento', 'nguyen', 'lozano', 'rojas', 'simon', 'evidence', 'internet', 'search']
['shows', 'information', 'seeking', 'responses', 'local', 'covid', 'cases', 'proceedings', 'national', 'academy']
['sciences', 'epidemic', 'psychology', 'works', 'twitter']
['bessi', 'ferrara', 'social', 'distort', 'presidential', 'election', 'online', 'discussion', 'first', 'monday']
[]
['exchange', 'power', 'social', 'transaction', 'publishers']
['bleidorn', 'klimstra', 'denissen', 'rentfrow', 'potter', 'gosling', 'personality', 'maturation']
['around', 'world', 'cross', 'cultural', 'examination', 'social', 'investment', 'theory', 'psychological', 'science']
[]
['borelli', 'sbarra', 'trauma', 'history', 'linguistic', 'focus', 'moderate', 'course', 'psychological']
['adjustment', 'divorce', 'journal', 'social', 'clinical', 'psychology']
['braun', 'clarke', 'using', 'thematic', 'analysis', 'psychology', 'qualitative', 'research', 'psychology']
[]
['broniatowski', 'jamison', 'alkulaib', 'benton', 'quinn', 'dredze']
['weaponized', 'health', 'communication', 'twitter', 'russian', 'trolls', 'amplify', 'vaccine', 'debate', 'american', 'journal']
['public', 'health']
['brooks', 'webster', 'smith', 'woodland', 'wessely', 'greenberg', 'rubin']
['psychological', 'impact', 'quarantine', 'reduce', 'rapid', 'review', 'evidence', 'lancet']
['language', 'communicating', 'threat', 'public', 'discourse', 'springer']
['lerman', 'ferrara', 'tracking', 'social', 'media', 'discourse', 'about', 'covid', 'pandemic', 'development']
['public', 'coronavirus', 'twitter', 'public', 'health', 'surveillance', 'e19273']
['19273']
['eysenbach', 'pandemics', 'twitter', 'content', 'analysis', 'tweets', 'during']
['outbreak']
['aiello', 'varga', 'quercia', 'social', 'dimensions', 'conversations', 'relationships']
['proceedings', 'conference']
['cinelli', 'quattrociocchi', 'galeazzi', 'valensise', 'brugnoli', 'schmidt', 'zollo']
['scala', 'covid', 'social', 'media', 'infodemic', 'arxiv', 'preprint', 'arxiv', '05004']
['coppersmith', 'dredze', 'harman', 'quantifying', 'mental', 'health', 'signals', 'twitter', 'proceedings']
['workshop', 'computational', 'linguistics', 'clinical', 'psychology', 'linguistic', 'signal', 'clinical', 'reality', 'pages']
[]
['schiano', 'covid', 'hangover', 'rising', 'alcohol', 'disorder', 'alcohol', 'associated']
['liver', 'disease', 'hepatology']
['rappaz', 'aiello', 'quercia', 'coloring', 'links', 'capturing', 'social', 'perceived']
['proceedings', 'conference', 'computer', 'supported', 'cooperative', 'social', 'computing']
['pages']
['deutsch', 'trust', 'suspicion', 'journal', 'conflict', 'resolution']
['dredze', 'bergsma', 'carmen', 'twitter', 'geolocation', 'system', 'applications', 'public']
['health', 'workshops', 'twenty', 'seventh', 'conference', 'artificial', 'intelligence']
['dutheil', 'mondillon', 'navel', 'second', 'tsunami', 'pandemic', 'psychological']
['medicine', 'pages']
['elsherief', 'kulkarni', 'nguyen', 'belding', 'lingo', 'target', 'based', 'linguistic', 'analysis']
['speech', 'social', 'media', 'twelfth', 'international', 'conference', 'social', 'media']
['engle', 'stromme', 'staying', 'mobility', 'effects', 'covid', 'available']
['ferrara', 'covid', 'twitter', 'conspiracies', 'social', 'media', 'activism', 'arxiv', 'preprint', 'arxiv', '09531']
[]
['ferrara', 'varol', 'davis', 'menczer', 'flammini', 'social', 'communications']
['epidemic', 'psychology', 'works', 'twitter']
['fetzer', 'hensel', 'hermle', 'coronavirus', 'perceptions', 'economic', 'anxiety', 'review', 'economics']
['statistics', 'pages']
['figea', 'kaati', 'scrivens', 'measuring', 'online', 'affects', 'white', 'supremacy', 'forum', 'conference']
['intelligence', 'security', 'informatics', 'pages']
['finlay', 'gilmore', 'covid', 'alcohol', 'dangerous', 'cocktail']
['fiske', 'cuddy', 'glick', 'universal', 'dimensions', 'social', 'cognition', 'warmth', 'competence', 'trends']
['cognitive', 'sciences']
['frimer', 'schaefer', 'oakes', 'moral', 'actor', 'selfish', 'agent', 'journal', 'personality', 'social', 'psychology']
[]
['liang', 'saroha', 'people', 'react', 'virus', 'outbreaks']
['twitter', 'computational', 'content', 'analysis', 'american', 'journal', 'infection', 'control']
['galea', 'merchant', 'lurie', 'mental', 'health', 'consequences', 'covid', 'physical', 'distancing']
['prevention', 'early', 'intervention', 'internal', 'medicine']
['liang', 'kruse', 'mapping', 'county', 'level', 'mobility', 'pattern', 'changes', 'united']
['states', 'response', 'covid', 'sigspatial', 'special']
['gibbs', 'thematic', 'coding', 'categorizing', 'analyzing', 'qualitative', 'london', 'pages']
['french', 'gergle', 'oberlander', 'language', 'emotion', 'short', 'texts', 'proceedings']
['conference', 'computer', 'supported', 'cooperative', 'pages']
['goffman', 'stigma', 'notes', 'management', 'spoiled', 'identity', 'simon', 'schuster']
['gonzalez', 'hidalgo', 'barabasi', 'understanding', 'individual', 'human', 'mobility', 'patterns', 'nature']
[]
['graham', 'haidt', 'nosek', 'liberals', 'conservatives', 'different', 'moral', 'foundations']
['journal', 'personality', 'social', 'psychology']
['graham', 'haidt', 'koleva', 'motyl', 'wojcik', 'ditto', 'moral', 'foundations', 'theory']
['pragmatic', 'validity', 'moral', 'pluralism', 'advances', 'experimental', 'social', 'psychology', 'volume', 'pages']
['elsevier']
['grossman', 'rexer', 'thirumurthy', 'political', 'partisanship', 'influences', 'behavioral', 'responses']
['governors', 'recommendations', 'covid', 'prevention', 'united', 'states', 'available', '3578695']
['hebert', 'clemow', 'pbert', 'ockene', 'ockene', 'social', 'desirability', 'dietary', 'report']
['compromise', 'validity', 'dietary', 'intake', 'measures', 'international', 'journal', 'epidemiology']
['hochreiter', 'schmidhuber', 'short', 'memory', 'neural', 'computation']
['hofstede', 'hofstede', 'minkov', 'cultures', 'organizations', 'software', 'volume']
['mcgraw']
['holmes', 'connor', 'perry', 'tracey', 'wessely', 'arseneault', 'ballard', 'christensen']
['silver', 'everall', 'multidisciplinary', 'research', 'priorities', 'covid', 'pandemic', 'action', 'mental']
['health', 'science', 'lancet', 'psychiatry']
['jiang', 'assessment', 'public', 'attention', 'perception', 'emotional']
['behavioural', 'responses', 'covid', 'outbreak', 'social', 'media', 'surveillance', 'china', 'perception', 'emotional']
['behavioural', 'responses', 'covid', 'outbreak', 'social', 'media', 'surveillance', 'china']
['huang', 'bidirectional', 'models', 'sequence', 'tagging', 'arxiv', 'preprint', 'arxiv', '01991']
[]
['auriemma', 'cashaw', 'report', 'underreporting', 'depression', 'journal']
['personality', 'assessment', 'epidemic', 'psychology', 'works', 'twitter']
['husnayain', 'applications', 'google', 'search', 'trends', 'communication', 'infectious']
['disease', 'management', 'study', 'covid', 'outbreak', 'taiwan', 'international', 'journal', 'infectious', 'diseases']
[]
['jimeno', 'yepes', 'mackinlay', 'identifying', 'diseases', 'drugs', 'symptoms', 'twitter']
['studies', 'health', 'technology', 'informatics']
['johnson', 'fendrich', 'modeling', 'sources', 'report', 'survey', 'epidemiology', 'annals']
['epidemiology']
['tobin', 'massey', 'anderson', 'measuring', 'emotional', 'expression', 'linguistic']
['inquiry', 'count', 'american', 'journal', 'psychology', 'pages']
['huremovi', 'psychology', 'pandemic', 'psychiatry', 'pandemics', 'pages', 'springer']
['kornfield', 'gustafson', 'before', 'relapse']
['language', 'online', 'discussion', 'forum', 'predicts', 'risky', 'drinking', 'among', 'those', 'recovery', 'health']
['communication']
['kouzy', 'jaoude', 'kraitem', 'karam', 'zarka', 'traboulsi']
['baddour', 'coronavirus', 'viral', 'quantifying', 'covid', 'misinformation', 'epidemic', 'twitter', 'cureus']
[]
['ubler', 'wessler', 'avioli', 'death', 'dying']
['goodchild', 'spatial', 'temporal', 'socioeconomic', 'patterns', 'twitter', 'flickr']
['cartography', 'geographic', 'information', 'science']
['impact', 'covid', 'epidemic', 'declaration', 'psychological']
['consequences', 'study', 'active', 'weibo', 'users', 'international', 'journal', 'environmental', 'research', 'public', 'health']
[]
['liang', 'effect', 'covid', 'youth', 'mental', 'health']
['psychiatric', 'quarterly', 'pages']
['goyal', 'joshi', 'lewis', 'zettlemoyer', 'stoyanov', 'roberta']
['robustly', 'optimized', 'pretraining', 'approach', 'arxiv', 'preprint', 'arxiv', '11692']
['utkepohl', 'introduction', 'multiple', 'series', 'analysis', 'springer', 'science', 'business', 'media']
['maslow', 'theory', 'human', 'motivation', 'psychological', 'review']
['mcconnell', 'banks', 'avian', 'planning', 'possible', 'pandemic', 'trading', 'technology']
['mohammad', 'turney', 'crowdsourcing', 'emotion', 'association', 'lexicon', 'computational', 'intelligence']
[]
['moinet', 'pastor', 'satorras', 'barrat', 'effect', 'perception', 'epidemic', 'spreading', 'temporal', 'networks']
['physical', 'review', '012313']
['connor', 'balasubramanyan', 'routledge', 'smith', 'tweets', 'polls', 'linking', 'sentiment']
['public', 'opinion', 'series', 'fourth', 'international', 'conference', 'weblogs', 'social', 'media']
['oyeyemi', 'gabarron', 'ebola', 'twitter', 'misinformation', 'dangerous', 'combination']
['g6178']
['painter', 'political', 'beliefs', 'affect', 'compliance', 'covid', 'social', 'distancing', 'orders', 'available']
['3569098']
['palshikar', 'simple', 'algorithms', 'detection', 'series', 'advanced']
['analysis', 'business', 'analytics', 'intelligence', 'volume']
['paszke', 'gross', 'chintala', 'chanan', 'devito', 'desmaison', 'antiga', 'lerer']
['automatic', 'differentiation', 'pytorch', 'proceedings', 'advances', 'neural', 'information', 'processing', 'systems']
['autodiff', 'workshop', 'epidemic', 'psychology', 'works', 'twitter']
['pennington', 'socher', 'manning', 'glove', 'global', 'vectors', 'representation', 'proceedings']
['conference', 'empirical', 'methods', 'natural', 'language', 'processing', 'pages', 'association', 'computational']
['linguistics']
['perrin', 'anderson', 'share', 'adults', 'using', 'social', 'media', 'including', 'facebook']
['mostly', 'unchanged', 'since', 'https', 'pewresearch']
['share', 'adults', 'using', 'social', 'media', 'including', 'facebook', 'mostly', 'unchanged', 'since']
['plutchik', 'emotions', 'university', 'press', 'america']
['pulido', 'villarejo', 'carballido', 'redondo', 'covid', 'infodemic', 'retweets']
['science', 'based', 'information', 'coronavirus', 'false', 'information', 'international', 'sociology']
['0268580920914755']
['nationwide', 'survey', 'psychological', 'distress', 'among', 'chinese']
['people', 'covid', 'epidemic', 'implications', 'policy', 'recommendations', 'general', 'psychiatry']
['rezapour', 'diesner', 'enhancing', 'measurement', 'social', 'effects', 'capturing', 'morality']
['proceedings', 'tenth', 'workshop', 'computational', 'approaches', 'subjectivity', 'sentiment', 'social', 'media']
['analysis', 'pages']
['russell', 'mining', 'social', 'mining', 'facebook', 'twitter', 'linkedin', 'google', 'github']
['reilly', 'media']
['alani', 'alleviating', 'sparsity', 'twitter', 'sentiment', 'analysis', 'workshop', 'proceedings']
[]
['salathe', 'bengtsson', 'bodnar', 'brewer', 'brownstein', 'buckee', 'campbell', 'cattuto']
['khandelwal', 'mabry', 'digital', 'epidemiology', 'comput', 'e1002616']
['scepanovic', 'martin', 'lopez', 'quercia', 'baykaner', 'extracting', 'medical', 'entities', 'social', 'media']
['proceedings', 'conference', 'health', 'inference', 'learning', 'pages']
['schutz', 'luckmann', 'zaner', 'engelhardt', 'structures', 'world', 'number', 'northwest', 'university', 'studies', 'phenomenology', 'existential', 'philosophy', 'northwestern', 'university', 'press']
['9780810106222', 'https', 'books', 'google', 'books', 'lgxbxi0xsh8c']
['gustafson', 'hawkins', 'cleary', 'mctavish', 'pingree', 'eliason']
['lumpkins', 'effects', 'prayer', 'religious', 'expression', 'within', 'computer', 'support', 'groups', 'women', 'breast']
['cancer', 'psycho', 'oncology', 'journal', 'psychological', 'social', 'behavioral', 'dimensions', 'cancer']
[]
['rudzicz', 'detecting', 'anxiety', 'through', 'reddit', 'proceedings', 'fourth', 'workshop', 'compu', 'tational', 'linguistics', 'clinical', 'psychology', 'linguistic', 'signal', 'clinical', 'reality', 'pages']
['shultz', 'baingana', 'neria', 'ebola', 'outbreak', 'mental', 'health', 'current', 'status', 'recom', 'mended', 'response']
['simms', 'ramstedt', 'richards', 'martinez', 'giraud', 'carrier', 'detecting', 'cognitive', 'distortions']
['through', 'machine', 'learning', 'analytics', 'international', 'conference', 'healthcare', 'informatics']
['pages']
['smith', 'shinebourne', 'interpretative', 'phenomenological', 'analysis', 'american', 'psychological', 'association']
[]
['sommariva', 'vamos', 'mantzarlis', 'martinez', 'tyson', 'spreading', 'exploring']
['health', 'messages', 'social', 'media', 'implications', 'health', 'professionals', 'using', 'study', 'american', 'journal']
['health', 'education']
['strong', 'epidemic', 'psychology', 'model', 'sociology', 'health', 'illness']
['tajfel', 'turner', 'austin', 'worchel', 'integrative', 'theory', 'intergroup', 'conflict', 'organizational']
['identity']
['tausczik', 'pennebaker', 'psychological', 'meaning', 'words', 'computerized', 'analysis']
['methods', 'journal', 'language', 'social', 'psychology', 'epidemic', 'psychology', 'works', 'twitter']
['economist', 'millions', 'stuck', 'online', 'wellness', 'dustry', 'booming', 'https', 'economist', 'international']
['millions', 'stuck', 'online', 'wellness', 'industry', 'booming']
['bavel', 'baicker', 'boggio', 'capraro', 'cichocka', 'cikara', 'crockett']
['douglas', 'druckman', 'using', 'social', 'behavioural', 'science', 'support', 'covid', 'pandemic', 'response']
['nature', 'human', 'behaviour', 'pages']
['varol', 'ferrara', 'davis', 'menczer', 'flammini', 'online', 'human', 'interactions', 'detection']
['estimation', 'characterization', 'eleventh', 'international', 'conference', 'social', 'media']
['immediate', 'psychological', 'responses', 'associated']
['factors', 'during', 'initial', 'stage', 'coronavirus', 'disease', 'covid', 'epidemic', 'among', 'general', 'population']
['china', 'international', 'journal', 'environmental', 'research', 'public', 'health']
['waterloo', 'baumgartner', 'peter', 'valkenburg', 'norms', 'online', 'expressions', 'emotion']
['comparing', 'facebook', 'twitter', 'instagram', 'whatsapp', 'media', 'society']
['windsor', 'dowell', 'graesser', 'language', 'autocrats', 'leaders', 'language', 'natural', 'disaster', 'crises']
['hazards', 'crisis', 'public', 'policy']
['wojcik', 'hughes', 'sizing', 'twitter', 'users', 'washington', 'research', 'center']
['theis', 'kordy', 'language', 'eating', 'disorder', 'blogs', 'psychological', 'implications', 'social', 'online']
['activity', 'journal', 'language', 'social', 'psychology']
['propagating', 'debunking', 'conspiracy', 'theories', 'twitter', 'during', 'virus', 'outbreak']
['cyberpsychology', 'behavior', 'social', 'networking']
['torres', 'menczer', 'prevalence', 'credibility', 'information', 'twitter', 'during']
['covid', 'outbreak', 'arxiv', 'preprint', 'arxiv', '14484']
['acknowledgments']
['thank', 'sarah', 'konrath', 'rosta', 'farzan', 'licia', 'capra', 'their', 'useful', 'feedback', 'manuscript', 'research']
['partly', 'supported', 'grant', 'green', 'routes', '869764']
['availability']
['daily', 'aggregates', 'measurements', 'available', 'https', 'figshare', '14892642']
['tweet', 'available', 'https', 'github', 'echen102', 'covid', 'tweetids', 'other', 'datasets']
['visualizations', 'available', 'project', 'social', 'dynamics', 'epidemicpsychology']
['competing', 'interests']
['author', 'declare', 'competing', 'interests', 'epidemic', 'psychology', 'works', 'twitter']
['supplementary', 'materials']
['spatial', 'representativeness', 'twitter', 'geographical', 'penetration', 'twitter']
['reflects', 'spatial', 'distribution', 'population', 'compared', 'activity', 'state']
['census', 'population', 'figure', 'shows', 'number', 'twitter', 'users', 'volume', 'their', 'tweets']
['correlate', 'strongly', 'census', 'population', 'population', 'estimates', 'level', 'states']
['https', 'census']
[]
['population']
[]
[]
[]
[]
[]
['tweets']
[]
[]
[]
[]
[]
['population']
[]
[]
[]
[]
[]
[]
['users']
[]
[]
[]
[]
['figure', 'correlation', 'census', 'population', 'states', 'estimated']
['number', 'tweets', 'posted', 'those', 'states', 'number', 'unique', 'twitter', 'users', 'posted']
['least', 'tweet', 'right', 'during', 'period', 'analysis', 'linear', 'shown', 'together']
['coefficient', 'determination', 'linear', 'regression']
['pearson', 'correlation', 'coefficient']
['coefficient', 'number', 'tweets', 'twitter', 'users', 'scale', 'almost', 'linearly']
['population', 'estimates']
['signals', 'racism', 'twitter', 'discussions', 'corroborate', 'qualitative', 'intuition', 'first', 'phase']
['characterized', 'discussions', 'depicted', 'pandemic', 'foreign', 'problem', 'often', 'using', 'racist', 'undertones']
['measured', 'volume', 'tweets', 'containing', 'hashtags', 'clear', 'indicators', 'content', 'either', 'racist']
['aimed', 'antagonizing', 'china', 'manually', 'selected', 'those', 'hashtags', 'hashtags', 'appeared']
['least', 'times', 'dataset', 'figure', 'shows', 'normalized', 'volume', 'those', 'hashtags']
['during', 'first', 'phase', 'related', 'mentions', 'focus', 'twitter', 'discussions', 'china', 'asian']
['foreigners', 'their', 'peaks']
['breakdown', 'phases', 'state', 'during', 'period', 'analysis', 'country', 'fragmented', 'regions']
['dealing', 'different', 'stages', 'outbreak', 'policies', 'contrast', 'varied', 'across', 'states', 'assess']
['whether', 'those', 'differences', 'impacted', 'unfolding', 'psycho', 'social', 'epidemics', 'across', 'states', 'computed']
['measures', 'represent', 'relative', 'presence', 'three', 'phases', 'refusal', 'anger', 'acceptance']
['state', 'individually', 'results', 'shown', 'figure', 'despite', 'minor', 'differences', 'state', 'level', 'curves']
['indicate', 'three', 'phases', 'place', 'states', 'sequence', 'phases', 'consistent', 'across', 'states']
['refusal', 'followed', 'anger', 'which', 'followed', 'acceptance', 'there', 'little', 'variation']
['times', 'transition', 'between', 'phases', 'epidemic', 'psychology', 'works', 'twitter']

# LSA Model
number_of_topics=1
words=word_count
model=create_gensim_lsa_model(clean_text,number_of_topics,words)
words_from_law =dict(model.show_topic(0, topn=words))##dict and encoding matrix values

dict(model.show_topic(0, topn=5))

{'covid': 0.4452922659095092,
 'pandem': 0.3598238418087631,
 'health': 0.3346202460677652,
 'polici': 0.2629476874262243,
 'impact': 0.2151343253537285}

from wordcloud import WordCloud
text = dict(model.show_topic(0, topn=20))
l=list(text.keys())
wordcloud = WordCloud(width=150, height=200,max_font_size=25, max_words=20, background_color="white").generate(" ".join(l))
plt.imshow(wordcloud, interpolation='bilinear')
plt.axis("off")
plt.savefig('graph20.png')

# LSA Model
number_of_topics = 20 #
words = word_count
model = create_gensim_lsa_model(clean_text,number_of_topics,words)

a=pd.DataFrame()

for i in range(number_of_topics):
    words_psychology =dict(model.show_topic(i, topn=words))
    b=pd.DataFrame(words_psychology,index=[i])
    a=a.append(b)

a=a.transpose()

top_words = dict(model.show_topic(0,topn=5))

df = pd.DataFrame(columns=list(top_words.keys()), 
                  index = list(top_words.keys()))

l = list(top_words.keys())
print('cosine-similarity')
for i in l:
    for j in l:
            matrix=np.array([a.loc[i],a.loc[j]])
            n = s.metrics.pairwise.cosine_similarity(matrix, matrix, dense_output=True)
            df.loc[[i],[j]] = n[0,1]
print(df)

dfi.export(df, 'df_styled23.png')

cosine-similarity
              covid       pandem      health      polici      impact
covid             1  0.000928622  -0.0102666  0.00596031   0.0383039
pandem  0.000928622            1 -0.00728671   0.0283235 -0.00412654
health   -0.0102666  -0.00728671           1     0.04196  -0.0366029
polici   0.00596031    0.0283235     0.04196           1   0.0375765
impact    0.0383039  -0.00412654  -0.0366029   0.0375765           1